Final Project Document (Autosaved) 1

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Faculty of Engineering, the Built Environment & IT

Technology for tomorrow

Department of Mechatronics

Microcontroller-Based Control for Robot Arm

Compiled by:Todd T Munemo

Supervisor:Dr. Farouk Smith

2012


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i Authentication

I Todd Munemo hereby declare that all work done in this project is my own and that I had no

assistance from outsiders (unless authorized by the Mechatronics department). I declare that

all references have been duly acknowledged.

Signed

.........................................

Todd Munemo


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Contentsi Authentication ............................................................................................................................................ 1

iii Synopsis ..................................................................................................................................................... 5

iv List of Acronyms ........................................................................................................................................ 6

1 Introduction ............................................................................................................................................... 7

2 Problem Analysis and System Requirements ............................................................................................. 8

2.1 Background ......................................................................................................................................... 8

2.2 Design Requirements .......................................................................................................................... 9

3 DESIGN CONCEPTS ................................................................................................................................... 10

3.1 Concept 1 FPGA Controller ............................................................................................................ 10

3.2 Concept 2MCU System .................................................................................................................. 11

3.3 Concept 3MCU + MULTIPLEXER .................................................................................................... 12

3.4 Comparison Matrix ........................................................................................................................... 13

4 FINAL DESIGN AND SPECIFICATIONS........................................................................................................ 14

4.1 Mechanical System ........................................................................................................................... 16

4.1.1 Robot Arm .................................................................................................................................. 16

4.1.2 Force Sensor ............................................................................................................................... 19

4.1.3 Servo Motors .............................................................................................................................. 21

4.2 Electrical System ............................................................................................................................... 21

4.2.1 The Robot Cable ......................................................................................................................... 22

4.2.2 The Arduino Mega 2560............................................................................................................. 23

4.2.3 H-Bridge Driver Module ............................................................................................................. 24

4.2.4 Optical Encoders ........................................................................................................................ 25

4.2.5 Limit Switches ............................................................................................................................ 27

4.2.6 Power Supplies ........................................................................................................................... 27

4.2.7 LCD ............................................................................................................................................. 27

4.3 The Hardware Control Circuit ....................................................................................................... 28

4.4 Control System and IT ....................................................................................................................... 28

4.4.1 Main Program ............................................................................................................................ 29

4.4.2 The Homing Subroutine ............................................................................................................. 30


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4.4.3 The Pick Subroutine ................................................................................................................... 32

4.4.4 The Place Subroutine ................................................................................................................. 34

4.5 Operation Description ....................................................................................................................... 35

4.5.1 Operation Sequence .................................................................................................................. 35

4.5.2 Safety ......................................................................................................................................... 35

5 Design and Development Procedure ....................................................................................................... 36

5.1 Introduction ...................................................................................................................................... 36

5.2 Mechanical ........................................................................................................................................ 36

5.1.2 Gear transmission mechanisms ................................................................................................. 36

5.2 Electrical ............................................................................................................................................ 43

5.2.1 Encoder Circuit Design ............................................................................................................... 43

5.2.2 Limit switch and Pushbutton circuit design ............................................................................... 47

5.2.3 Force Sensor Circuit design ........................................................................................................ 49

5.2.4 Power Supply unit selection ....................................................................................................... 51

5.3 Robot Kinematics .............................................................................................................................. 51

5.3.1 DenavitHartenberg Forward and Inverse Kinematics ............................................................. 51

5.3.2 Geometric approach to inverse kinematics ............................................................................... 55

5.3.4 Sample calculations .................................................................................................................... 58

5.4 Position Control of the robot arm ..................................................................................................... 59

5.4.1 Position Control System ............................................................................................................. 59

5.4.2 Optical Encoder decoding .......................................................................................................... 60

5.4.4 Calibration Procedure ................................................................................................................ 61

5.4.4 Base Position Control ................................................................................................................. 63

5.4.5 Shoulder Position Control .......................................................................................................... 66

5.4.6 Elbow Position Control ............................................................................................................... 68

5.4.7 Gripper Control .......................................................................................................................... 69

5.6 IT........................................................................................................................................................ 69

5.6.1 User Interface and Serial Communication ................................................................................. 69

6 Performance Evaluation, Experiments and Data Analysis ....................................................................... 71

6.1 Duty Cycle Variation with Error ........................................................................................................ 71

6.2 Accuracy ............................................................................................................................................ 72

6.2.1 Comparison of Theoretical and Calibration Performance ......................................................... 73


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6.3 Speed................................................................................................................................................. 75

7 Conclusions .............................................................................................................................................. 76

8 References ............................................................................................................................................... 78

APPENDIX ACOMPONENT SPECIFICATIONS ............................................................................................ 81

A-1 FlexiForce A401 sensor ..................................................................................................................... 82

A-2 Arduino Mega ................................................................................................................................... 83

A-3 H-Bridge Driver ................................................................................................................................. 84

A-4 Meanwell Power Supply ................................................................................................................... 85

A-1 Arduino Mega Schematic ................................................................................................................. 86

APPENDIX BHARDWARE CONTROL CIRCUIT BILL OF MATERIALS ........................................................... 87

APPENDIX C - EXPERIMENTS ....................................................................................................................... 88

C-1 Encoder Circuit Testing ..................................................................................................................... 89

C-2 Base Calibration ................................................................................................................................ 91

C-3 Shoulder Calibration ......................................................................................................................... 92

C-4 Elbow Calibration .............................................................................................................................. 92

C-5 Accuracy and Duty Cycle ................................................................................................................... 93

C-6 Theoretical against Calibration performance ................................................................................... 94

APPENDIX D PROGRAM CODE.................................................................................................................. 95

APPENDIX ETHE HARDWARE CONTROL CIRCUIT .................................................................................... 96


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iii Synopsis

A robot arm controller was designed as a final year project. The project involved designing a

robot controller that would control a five axis robot to perform pick and place tasks. The

designed controllers performance is to be compared with the original controller which was

designed by Eshed Robotec. The robot had a speed of 330mm/sec and a repeatability of +/-0.05mm when it was manufactured (Eshed Robotec, 1995:2-3). The programming language has

to be based on the C programming environment.

Three concepts were evaluated and the final design was adapted from the best design concept

which has microcontroller at its core. This design was chosen because the Arduino Mega

microcontroller had enough ports to accommodate all the inputs and also because there is a lot

of support available for the Arduino on the internet.

The design allows the user to enter coordinates for pick and place tasks in the robot workspace.The inverse kinematics method then converts the Cartesian coordinates entered by the user

into joint angles to which the robot has to be moved. The encoders on the motors are used as

feedback to control the positioning of the robot joints. Communication between the user and

computer is done through a user interface created on the Arduino serial monitor.

The performance of the robot was evaluated and satisfactory results were attained. The key

performance parameters were achieved to a satisfactory degree due to the fact that the robot

has gone through a wear and tear process over the years. The controller designed managed to

execute the pick and place task as required.


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iv List of Acronyms

Acronym Definition

MCU Microcontroller

FPGA Field programmable gate array

I/O Input/output

IC Integrated Circuit

kB kilobyte

PWM Pulse width modulation

USB Universal Serial Bus

ICSP In-circuit Serial programming

IK Inverse Kinematics

IP Intellectual Property

D-H Denavit-Hartenberg


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1 Introduction

The purpose of this project is to design a microcontroller based controller for a five axis robot

arm to perform a simple pick and place task. According to Spong et al (2006:10), a robot is a

reprogrammable, multifunctional, manipulator designed to move material, parts, tools, or

specialised devices through variable programmed motions for the performance of a variety oftasks. The controller is to be implemented on a SCORBOT ER III robot arm designed by Eshed

Robotics. The purpose of the controller design is to replace the old controller which was

removed from the robot. This design task is to be completed as a final year BEng Mechatronics

project requirement. A microcontroller (MCU) is a small computer on a singleintegrated circuit

containing a processor core, memory, and programmableinput/output peripherals. The MCU is

the backbone of the whole controller design; it performs all the logical operations involved in

controlling the robot to perform a pick and place task.

Robots are extensively used in the manufacturing industry where a lot of repetitive work is

done because of their high repeatability and accuracy when compared to humans. Robots are

also becoming important in most industries as well (Fernandez et al, 2012:50). The Robot arm is

the most common amongst all manufacturing robots and is used for various manufacturing

processes which include spray painting, welding and assembly operations (Iqbal et al,

2012:300). Usually servo motors are used to control the movement of all the robot joints as the

feedback obtained from their encoders is vital for the precise control of the robots motion.

Sensors are also incorporated in robot arms to detect any foreign obstacles and to prevent

dropping or breaking any loaded components in its gripper.

This document analyses the problem at hand and various concepts are generated to developthe final controller design, with specific attention given to the key performance parameters

required as highlighted in the problem statement. The final design is developed from the best

concept design which is selected through the aid of a comparison matrix. The entire design is

split into the analysis of mechanical, electrical and Information Technology (IT) components. A

robot hardware control circuit was designed through the application of standard engineering

principles.

The performance of the designed and assembled model was finally evaluated. The robots

repeatability was found to be +/- 12.6mm which differs greatly from that of the manufacturer,

which is rated +/- 0.05mm. The speed of the robot was found to be 26.65 mm/s, which is very

slow compared to the manufacturers rated speed of 330mm/sec. The huge difference between

the manufacturers repeatability and that of the designed controller can be attributed to

reduction in accuracy of the base which as it had the largest positioning standard error of +/-

3.4mm.The base was driven at a low speed to minimise the positioning error, resulting in a
http://en.wikipedia.org/wiki/Integrated_circuithttp://en.wikipedia.org/wiki/Input/outputhttp://en.wikipedia.org/wiki/Input/outputhttp://en.wikipedia.org/wiki/Integrated_circuit


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great reduction of the robots speed. Overally the pick and place task was successfully

completed.

2 Problem Analysis and System Requirements

The aim of the overall system is to design a microcontroller or FPGA based controller for a 5-

axis robot arm to perform a simple pick and place task.

2.1 Background

The SCORBOT-ER III is a robot teaching device that was developed in the early 80s due to the

progress achieved in robotics and industry globally. This robot came with its own dedicated

controller which had a unique program modular training that allowed instructors to conduct

robotics courses for students. This allowed the students to get the opportunity of handling

robot systems.

The robots joints are all revolution in type. The arm is constructed as a five degrees of freedom

articulated arm (base, shoulder, elbow, wrist roll and pitch) which are all driven by DC motors

with shaft encoders on their axes.

Figure 1: Scorbot ER-III robot arm


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2.2 Design Requirements

The main focus of this design project is to design a controller for the SCORBOT ER-III. The

available components are:

The robotic arm (SCORBOT ER-III)

The Altera Cyclone III development board or MCU development board H-bridge drivers

The robot controller design mainly focuses on the IT and electrical circuit design aspects while

the mechanical aspect entails gear ratio calculations.

The following calculations are critical to the design process:

Inverse Kinematics calculations are required to determine the joint angle parameters to

facilitate the pick and place tasks of the robot.

The gear train transmission relationships need to be determined for the calculation of

the encoder resolution for the various joints. The resolution is defined as the smalleststep achievable by turning gears (or engines, or joints, etc.).The usual practice is to

define this step in degrees (angular resolution) or units of length (linear resolution).

The electrical part of the design involves the development of a control circuit that interfaces the

inputs and outputs of the system with the MCU. The outputs from the quadrature encoders,

limit switches and force sensor are to be fed back into the MCU. Limit switches help to

determine the robots home position and also assist in restraining the joint motions to their

maximum angle of rotation to avoid joint collisions. Quadrature encoders provide feedback on

the joint DC motors direction speed and position. The force sensor regulates the grippershandling force.

The control circuit should generate pulse width modulated (PWM) signals which required to run

the DC motors that drive the joints of the robot. PWM signals are varying digital signals which

average the voltage to the servomotors and thus control the motor speed. The PWM signal

generated by the MCU is supplied to the servomotors through the H-Bridge drivers, since an

MCU only supplies a maximum of 5V on its output and does not have enough power to run the

12V DC motors.

The software design aspect involves developing algorithms for inverse kinematics computations

and motor position control. The control system of the robot should be implemented in C

language programming.


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The technical performance measures that need to be taken into consideration for the controller

design are:

Accuracy: - the robot should accurately pick an object at the specified pick

position and must also accurately place the object.

Repeatability: -The pick and place task must be performed repeatedly with thespecified level of accuracy.

Speed: - The pick and place task should be performed as fast as possible.

Efficiency: -An optimized trajectory is required for the pick and place task.

3 DESIGN CONCEPTS

The design concepts generation involves the development of a hardware control circuit for the

SCORBOT ER-III robot arm. Three concepts are generated and the best concept is selected with

the aid of a comparison matrix.

3.1 Concept 1 FPGA Controller

Figure 2 : The FPGA controller concept

The first concept has a FPGA controller at its core and four H-bridge servo drivers (see Figure 2).

The main purpose of the central controller is to execute the computation of the motion

trajectory and inverse kinematics. The central controller integrated circuit (IC) comprises of two

intellectual properties (IPs); one is dedicated to the computation of inverse kinematics of the


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robot while the other is responsible for performing the functions of the trajectory motion in

software. The encoders provide feedback on the robot position to the central controller. At

least 34 digital 10 pins are required for the encoder feedback, PWM, motor control and limit

switch detection.FPGAs have sufficient ports; for example the Altera Stratix II EP2S60F672C5ES

FPGA has 718 I/O ports which are more than enough (Kung & Chen, 2008:292). FPGAs are notsuited for floating point computations which are required for the Inverse kinematics method of

expressing Cartesian coordinates in terms of the robot angle parameters (Toh et al, 2009:448).

FPGAs can perform floating point calculations but such a task requires a vast amount of logic

cells to conduct calculations. According to Edwards (2011:1) FPGA code requires specialised

talent; this is due to the time and tedious demands of the iterative nature of FPGA code

development and the associated long synthesis/simulation/execution design cycle, thus there is

a risk of not completing the project on time since the author is not familiar with FPGAs. The

development time of the FPGA hardware is long as different modules need to be fastened and

tested to perfection before the FPGA can be used. They are also generally expensive.

3.2 Concept 2 MCU System

Figure 3 : The MCU system concept

The second concept (see Figure 3) is similar in structure to the first, but it has a MCU at the

center of the robot control hardware. The MCU supplies PWM signals to the H-bridge drivers

and takes feedback from the quadrature encoders, limit switches and the force sensor. Unlike

the FPGA, MCUs address floating point calculations with well-developed vector math engines,

which means that their processors are well designed for simple math calculation (Edwards,

2011:1). FPGA development often takes much longer than microprocessor development for an

equivalent task using a high-level language like C or C++ (Edwards, 2011:1).The MCU also has in

built functions for quadrature encoder decoding and PWM signal generation required by the


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motors. MCUs are much lower in cost as compared to FPGAs for small applications and large

quantities. MCUs however are always sequential and therefore less flexible than FPGAs which

are can execute code in parallel or sequentially. Programming requires long lines of code which

complicates structuring and debugging. At least 34 digital IO pins are required and the main

problem of implementing the MCU concept lies in its shortage of sufficient I\O pins. Thisproblem can be solved by settling for bigger MCUs with more pins, but the problem is that they

come at a higher cost.

3.3 Concept 3MCU + MULTIPLEXER

Figure 4 : The MCU + MUX concept

The third concept (see Figure 4) tries to find a solution to the inadequacies of the second

concept by introducing a multiplexer such that a smaller MCU which comes at a lower cost canbe used. In order to read all the 8 digital inputs from encoders, a multiplexer board is added to

the MCU system presented earlier. This reduces the demand of pins on the MCU. The motors

are controlled by the MCU via H-bridge drivers. The multiplexer (MUX) is connected to the MCU

to facilitate signal selection by the MCU. The hardware implementation is less complex

compared to the FPGA design and is manageable. The third concept however requires more


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programming as the functionality of the multiplexer also has to be included in code. The other

disadvantage is that only one encoder channel is processed at a particular time, this increases

the cycle time of the pick and place task as the motors will have to be run sequentially since

one motor can be controlled at a particular time.

3.4 Comparison Matrix

The three concepts are evaluated with the aid of a comparison matrix (see Table 1), with 5

being the most favourable rating, 3 being the value given to second best concept on a particular

performance parameter and zero being the least. The three concepts are compared based on

the following parameters:

Easy hardware Implementation

Ease of programming

Processing speed

Flexibility Low Cost

Efficiency

Table 1 : The Comparison matrix

FPGA MCU MCU + MUX

Easy Hardware Implementation 0 5 0

Ease of Programming 0 5 3

Shorter cycle time 5 3 0

Flexibility 4 0 0

Efficiency 5 3 0

Cost 0 3 5

Total 14 19 8

The MCU concept most has the most favourable points for the ease at which the hardware can

be implemented parameter, the main reason being the fact that the MCU comes with most, if

not all its peripheral devices unlike the FPGA which does not come with all hardware

peripherals. The MCU +MUX is the second best because there is need for the addition of the

multiplexer unlike a bigger MCU which can be directly interfaced with the encoders since it has

enough pins. The FPGA has the least score on the Ease of programming parameter; the main

contributing factor is because it is easier to program a MCU compared to an FPGA. The

MCU+MUX concept was second best because there is need to program more code for channel

selection on the multiplexer, thus making it more complicated than the MCU concept.


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The FPGA concept is the most flexible since can be used to execute both sequential and parallel

code unlike the MCUs which execute the code sequentially. The FPGA has the shortest cycle

time since all motors can be controlled simultaneously because of its parallel functionality .The

FPGA is more expensive than a MCU(Edwards,2011:1) thus it has the lowest score on cost.

From table 1, the MCU system has the highest score therefore the ideas from this conceptgreatly contributed to the final design.

4 FINAL DESIGN AND SPECIFICATIONS

Motor 1(Base)

Motor 2(Shoulder)

Motor 3(Elbow)

Motor 4(Wrist Pitch)

Motor 5(Wrist Roll)

Motor 6 (Gripper)

MCU

(Arduino Mega 2560)6 rotary encoders

5 Limit Switches

Force Sensor

FlexiForce(A401)

Dual H-Bridge 2

L298

Dual H-Bridge 3

L298

Dual H-Bridge 1

L298

Figure 5 : Final controller design

The final design (see Figure 5) is very similar to concept 2 and has an Arduino Mega 2560 as the

core of the hardware design. The Arduino MEGA is a MCU board based on the Atmega2560.This

MCU overcomes the main problem of the second concept as it has 54 I/O pins which are

sufficient for controlling the robot. Two dual H-Bridge driver modules based on the ST L298 dual

full bridge driver are used to power the robots DC motors. The sensors, limit switches and

encoders are connected as inputs to the MCU.The MeanWell power supply, which is a 12VDC

power supply is used to power the motor H-Bridge drivers. For the final design only four axes

are controlled and they are:

Shoulder

Base

Elbow

Gripper


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The wrist roll is fixed at 180 degrees and the wrist pitch is fixed such that the gripper angle is

always -90 degrees. The four axes are sufficient for performing the pick and place task. This

decision reduces the complexity of the inverse kinematics and the motion control algorithm.

Figure 6: Final design model


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4.1 Mechanical System

4.1.1 Robot Arm

Figure 7 : Scorbot ER-III joint positions (Eshed Robotec: 1995)

The mechanical system of this project is SCORBORT ER-III (see Figure 7) robot which was

described earlier in the problem statement. This articulated arm has five degrees of freedom

(base, shoulder, elbow and the wrist which has two movements and the gripper which can be

considered as the sixth axis). With exception of the gripper which is moves linearly when in

motion, all the joints exhibit a rotational motion about their axes. The SCORBOT ER-III has a

mountable base with six holes to keep it secure from movement during operation. The axes of

the robot are driven by 12V DC servomotors with shaft encoders on their axles; the encoders

facilitate closed loop control of the servomotors. The servomotors have a reduction gear box so

that the output shaft of the gearbox rotates at lower speed than the armature coils of the

motors. A positive DC supply rotates the robot servomotors in one direction and a negative

supply rotates the robot in the other direction. The elbow is driven by a servomotor through an

indirect coupling system. Indirect coupling refers to a system where the motor is mounted

away from the joint and the motion of the motor is transmitted via transmission systems such

belts which have a small weight when compared to gears. The indirect coupling system is

implemented because it reduces the weight of the arm.The locations of the robot motors are


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shown in Figure 8.The mechanical arm has five limit switches with each joint having one; these

switches help to prevent collisions between joints. They also help in the determination of the

Hard Home position, which refers to the robot orientation when all limit switches are

activated.

Figure 8 : DC servomotor locations (www.repostorio.bib.upct.es/dspace)

Mechanical Structure: Vertically Articulated, 5 Axis PLUS Gripper = 6 Axis

Figure 9 : The Scorbot ER-III workspace (Eshed Robotec: 1995)


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The robot had the following specifications when it was manufactured by Eshed Robotec:

Working Envelope (see Figure 9):

Axis 1: Base Rotation 310 degrees

Axis 2: Shoulder Rotation +130 Degrees / -35 Degrees

Axis 3: Elbow Rotation +- 130 Degrees

Axis 4: Wrist Pitch +- 130 Degrees

Axis 5: Wrist Roll Unlimited

Axis 6: Gripper Open/Close + Measurement of gripper opening

Maximum Working Radius: 61mm (24.4")

Gripper Opening: 75mm (3") without rubber pads - 65mm (2.56")

with rubber pads

Maximum Work Load: 1kg (2.2 lbs.)

Transmission: Gears, Timing Belts and Lead Screw

Actuators: 6 DC Servo Motors with Closed-Loop Servo Control

Feedback: Optical Encoders on All Axes

Hard Home: Fixed Reference Position on all Axes

Repeatability: +- .05mm (+- 0.02")

Maximum Speed: 330mm/Sec. (13"/Sec)

Weight: Robot Arm: 11kg (24 lbs.) - Controller: 5kg (11 lbs.)


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4.1.2 Force Sensor

Figure 10 : FlexiForce A401 force sensor (Tekscan: 2012)

Tekscans FlexiForce A401 (see Figure 10) sensor is used to measure the gripping force of the

robot. This sensor is a durable piezoresistive sensor that senses a contact force. A piezoresistive

sensors resistance value changes when it is squeezed by a force. According to (Eshed

Robotec,2012: 2-3), the robot can pick a maximum of 1kg mass.For the selection of a force

sensor, a force analysis is done on the gripper. The force sensor should be able to detect the

maximum operating force of the gripper. The gripper exerts this force when handling the 1kg

mass.


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Figure 11: Gripper force diagram

The force sensor detects N , which is the compression force exerted on the vertical sides of themass M shown in figure 11.The force sensor is placed between one vertical side of the block

and the gripper rubber pads.F1 and F2 represent the frictional forces required to prevent the

mass from falling due to gravity. To determine the force N1 the following equations are used:

a represents the acceleration due to gravity, which is 9.81m/s

2 on earth. This equation is

derived from Newtons third law of motion.

Where F representsthe frictional force,N represents the normal force and =0.7 is the

coefficient of friction between rubber and wood (since the gripper has rubber pads and

the load being lifted is made of wood).

The summation of forces in the vertical direction is done to calculate the F2.


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Therefore: = 9.81 N

Making N subject of the formula:

Therefore, the maximum force that can be detected by the force sensor is 7N.The Tekscan A401

sensor was chosen because it can take a maximum of 110N.The forces to be exerted on the

gripper vary between 0-7N.These forces fall within the range of the selected force sensor which

is between 0N and 110N, which makes the selected sensor suitable for this application. The

specifications of the sensor can be found in APPENDIX A-1.

4.1.3 Servo Motors

The SCORBOT ER- III joints are run by Pittman G9000 series motors. These motors operate with

a voltage of 12V DC and the maximum current they can take is 2A (Eshed Robotec, 1995: F-

2).Therefore a power supply of at least 12VDC is required to power the motors.

4.2 Electrical System

Figure 12: Controller box


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The main elements of the electrical system are:

Robot cable

Arduino Mega 2560

H-Bridge Driver Modules

Optical Encoders

Limit Switches

Power Supply

The electrical system is the core of this project, and it is basically the integration of the various

electrical elements listed above to form a hardware control circuit. The electrical elements,

their functionality and integration into the final design are described in the report.

4.2.1 The Robot Cable

The operational and control commands of the robot are transmitted through this cable, which

is the link between the robot arm and the controller. The cable runs from the base of the robot

arm to the controller. The cable has 48 leads which are divided into six groups (one group for a

single motor).Each group contains eight leads:

2 leads supply voltage to the motor.

2 leads receive pulses from the optical encoder (channel 0 and

channel 1).

1 lead carries the signal from the limit switch.

1 lead supplies voltage to the encoder (VLED).

1 lead provides the ground for the limit switch.

1 lead provides the ground for the encoder.

Only four of the six groups of leads are required to control the base, shoulder, elbow and

gripper.


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4.2.2 The Arduino Mega 2560

Figure 13 : Arduino Mega 2560 front (www.arduino.com)

This MCU board (see Figure 13) is the heart of the robot control system. As earlier stated, the

board is based on the Atmega2560. The Arduino has 54 digital I/O pins, of which 14 can be

implemented as PWM outputs, 16 as analog inputs, 4 as UARTs(hardware serial ports), a

16MHz crystal oscillator, a USB connection, a power jack, an ICSP header, and a reset button.

The pins operate at 5V.Eeach pin has an internal pull-up resistor (20-50 k) and can provide or

receive a maximum of 40mA of current. This MCU has an input impedance which varies from

100k - 1M.The MCU board is any easy to use device, to get started it can be powered by

simply connecting it to a computer via a USB cable or a battery. The Mega series of the Arduinowas mainly chosen for this task because it has sufficient I/O pins to interface with the encoders,

limit switches and the force sensor. The Arduino is programmed in C language .The Schematic,

Reference Design & Pin Mapping and more information on the Arduino is provided in APPENDIX

A-2.
http://arduino.cc/en/uploads/Main/ArduinoMega2560_r2_front.jpg


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4.2.3 H-Bridge Driver Module

Figure 14 : Dual H-Bridge driver module (www.seeedstudio.com)

The MCU cannot supply enough power to run the motors and therefore two Dual H-Bridge

driver modules (see Figure 14) based on the ST L298 IC are used to provide the power required

to run the motors. The ST L298 is a high voltage and current dual full bridge driver which

accepts standard TTL logic levels and drives inductive loads such as DC motors. The enable pins

of the driver take a PWM signal which then drives the motor at speed proportional to the

signals duty cycle. Port A and port B are symmetrical on the module and have the same

functionality. The word ports refers to pins which are used to connect electrical wires coming

from the motors and the MCU to the H-bridge driver. Each port has 5 pins I1, I2, VCC, GND and

EA, both I1 and I2 are digital ports which are responsible for controlling the motor direction. IfI1 and 12 are equal, the motor stops rotating and if I1=1 and I2=0 the motor rotates in a

clockwise direction (see table 2).


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Table 2 : Dual H-Bridge driver module logic (www.seeedstudio.com)

GND and VCC are connected to the terminals of the robots motors. The features of and

datasheet can be found in Appendix A-3.

4.2.4 Optical Encoders

Figure 15 : Encoder discs for the SCORBOT ER -III (Eshed Robotec: 1995)

The optical encoders facilitate the closed loop control of the servomotors which control the

robotsjoints. The SCORBOT ER-III has two types of optical encoders (see Figure 15), one with

three slots and the other with six slots. All servomotors excluding the gripper motor use the six

slotted encoder disc type. The encoder disks are connected directly to the motor shaft and theyconsequently rotate at the same speed as the shaft. The encoder circuitry (see Figure 16)

comprises of a printed circuit board (PC 500) which has two LEDsand two phototransistors (P0

and P1). The encoder outputs two signals, one for each LEDphototransistor pair. The LEDs are

connected to a 5V voltage source and they act as light sources and are mounted at opposite

ends with the transistors. One LED-phototransistor couple is positioned near the outer

circumference of the disc and the other at the center. The phototransistors have three

connections (base, emitter and collector).


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Figure 16 : The encoder circuitry (Eshed Robotec: 1995)

The two LED- phototransistor pairs generate tracks signals that are 90 degrees out of phase;

this phenomenon is thoroughly described with diagrams in section 5.4.2. The speed and

direction of the motor can be determined by monitoring the relationship between the square

wave pulses. The angular motion can be measured by knowing the resolution of the encoder

disk and monitoring the number of pulses using the MCUs counter. The decoding scheme that

will be implemented in this design will involve capturing the falling edges of square wave A

using an interrupt service routine. This scheme is also described with diagrams in section 5.4.2

which explains how the position control is achieved through the use of optical encoders.


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4.2.5 Limit Switches

Figure 17 : Limit Switch

Each robot joint has a limit switch (see Figure17) fitted at its home position. Depression of all

the limit switches by the cam, represents the robots hard home position, which is areference point for the robot.

4.2.6 Power Supplies

A power supply is required to power the H-Bridge driver modules. The motors run on a 12V DC

voltage supply and can only take a maximum of 2A current. The Meanwell S-250-12 which is a

12VDC power supply is used to power the system and has the following specifications

(Meanwell, 2008:1):

90-132VAC / 176-264VAC input Selected by switch

Output 12V DC Rated current 18 A and the current operates on a 0-18A current

range

Short circuit, overload and over voltage protection

Cooling by free air convection

The full datasheet can be found in Appendix A-4. The MCU is powered by the USB cable

connected to the computer. The MCU supplies 5V to the rest of the circuit with its power

supply ports.

4.2.7 LCD

The Liquid crystal display (LCD) which is mounted on the front cover of the circuit box is used to

display feedback from the inverse kinematics calculations. This allows the user to check if there

is any error occurring from the calculations done by the MCU. The Grove serial LCD version 1.1

which is a 16x2 character display LCD is used for interfacing with the MCU, communication is

done serially at a baud rate of 9600kB/s. There is no particular reason why this baud rate was


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used; any standard baud rate will work. Communication only occurs when the arduino and the

serial LCD are sending information at the same baud rate.

The serial LCD is very easy to use and its interface with the Arduino only requires four pins, one

for transmitting (Tx pin), one for receiving (Rx pin), one for VCC and the last one for GND. It

contains a processor which takes serial data from the Arduino and displays it on the screen. It

also accepts serial commands for conducting tasks like cursor positioning and screen clearing,

which makes it very easy for displaying information.

4.3 The Hardware Control Circuit

The hardware control circuit was created using the Fritzing software which is used for designing

arduino circuits. The Fritzing software contains schematics for Arduino MCUs and most

electronic components. This software was used because the parts are readily available and the

circuit drawing task is only reduced to the selection and wiring of the required components,

which saves a lot of time. The hardware control circuit schematic shows how the motors,

encoders, LCD and limit switches are wired together to form an electrical circuit. The hardware

control circuit and the bill of materials of the control circuit can be found in appendix E.

4.4 Control System and IT

The IT part of the project deals with developing an algorithm which controls the pick and place

task. This algorithm is downloaded to the MCU and the required subroutines to control the

robot are executed. It also involves executing calculations for inverse kinematics and taking

input from sensors. The inputs from the sensors are used as feedback for controlling the robot

motors. The program was coded in the Arduino environment which is a C based language. Themain program can be divided into the pick, place and homing subroutines. Relative encoders

are used on the robot arm. According to Sahin & Kachroo (2007:173) when robot arm joint

movements are controlled by relative encoders, a convenient home position is achieved by

turning all the joints counter clockwise to their limits. The homing subroutine has to be

executed several times since the home position is the reference point for absolute positioning

of the relative encoders. After the picking of an object, the robot goes back to the home

position before it performs the placing task. All the robot arm movement subroutines were

designed by the author.


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4.4.1 Main Program

Start

Homing

Sequence

Display

feedback

from limit

switches

Wait until user

operator enters

pick and place

coordinates

Inverse

Kinematics

calculations

Display Input

from operator

Display Joint

angles

Pick Sequence

Is picking

sequence

complete?

No

Place

sequence

Is the placing

sequence

complete?

Yes

End

Yes

No

Display

feedback

Display

feedback

Figure 18: Flow diagram for the main program

The main program (see Figure 18) begins by executing the homing subroutine once the system

is started. On completion of the homing subroutine, the program prompts the operator to

provide Cartesian coordinates for the pick and place positions. Once these coordinates are

provided, the pick subroutine is executed. The place subroutine is executed once the picking is

completed. Flags are set to monitor the progress of the subroutines. This facilitates the control

of execution times for different subroutines, for example if the pick flag is set to high; thissignifies that the pick process is being executed and is thus being monitored. Thus, the place

algorithm will only begin when the pick flag is set to low, which indicates that the pick

algorithm is complete. Once placing is done, the program waits for the user to initiate another

pick and place task by pressing the start button.


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4.4.2 The Homing Subroutine

Start

No

Is base

homing

direction

forward?

Run

shoulder

motor

backward

Is shoulder

LS==LOW?

Run Elbow

motor

Forward

No

Is Elbow

LS==LOW?

Run Base

motor

backward

Run Base

motor

forward

Yes No

Is Base

LS==LOW?

Is Base

LS==LOW?

Yes

Yes

No

No

Is force>=Threshold

value?

End

No

Yes

No

Yes

Is pick==1?

Yes

Delay 10s

Run gripper

motor

backward

Is gripper

LS==LOW?

No

Figure 19: The homing subroutine flow diagram

The homing subroutine (see Figure 19) was decided upon realising that the robot uses relative

encoders. Relative encoders do not maintain position information when power is lost which

means the robots orientation information is also lost. Therefore there is need to define a


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reference point to which all robot positions are measured from. The home position is used as

the reference point. To control the movement, the robot has to be at the home position before

each pick or place task. Though this procedure is not time efficient, it provides an easy way of

positioning the robot for the pick and place tasks.

Figure 20: Robot homing sequence

Figure 20 shows robot in its home position (all limit switches are pressed in this position) and

the position before homing is indicated by the black frame. The shoulder joint is moved

backwards up until the shoulder limit switch is pressed which indicates that the shoulder home

position has been reached. On completion of the shoulder movement, the elbow is run forward

till the elbow limit switch is pressed. For the base the program checks the status of the base

homing switch, which is on the controller box. The base is rotated to the direction set by theuser, this is mainly due to the fact that while performing either the pick or place task, the base

is the only joint which rotates in two directions, and, therefore, there is need for a user input to

monitor the direction in which the base has to be rotated so that it can find the limit switch.

Once the base has reached its home position the program checks if the gripper is holding

anything by checking the force sensor value to find whether the force is equal or below the


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threshold value. If the gripper is not holding anything, the force will be lower than the threshold

value. If it is holding anything, the algorithm checks if the picking procedure is being executed.

If not, the gripper delays for 10s and opens so that the operator can take the picked component

on the gripper and the homing subroutine ends. In the case that the picking procedure is being

executed, the homing sequence ends without opening the gripper.

4.4.3 The Pick Subroutine

Call from

IK

Set_arm_1

Is base

direction

forward?

Run Base

motor

forward

Yes

Run base

backward

No

Is encoder

count ==base

position?

Is encoder

count==base

position?

NoNo

Run Shoulder

motor

forward

Yes

Yes

Is encoder

count ==

shoulder

position?

No

Run Elbow

motor

backward

Is encoder

count ==

Elbow

position?

No

Run gripper

motor

forward

Is force

sensor

value==to

force

threshold

value?

No

Call

homing

procedure

Figure 21: The pick subroutine flow diagram


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The pick subroutine (see Figure 21) is called from the inverse kinematics method set_arm_1 (x,

y, z) which takes the pick coordinates entered by the user as input and performs inverse

kinematics calculations. The pick algorithm rotates the base in the relevant direction. The

rotation stops once the calculated pulses from the inverse kinematics method are equal to the

pulses counted by the MCU. On completion of the base rotation, the shoulder is moved forwardtill it reaches its required destination. On completion of the shoulder motion, the elbow is

moved backwards till it reaches its final position. Finally the gripper is closed until the force

sensor reads a value equal to the set threshold value of the gripping force. The pick subroutine

calls the homing procedure once the item to be picked is held by the robot gripper.


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4.4.4 The Place Subroutine

Call from

IK

Set_arm_2

Is base

direction

forward?

Run Base

motor

forward

Yes

Run base

backward

No

Is encoder

count ==base

position?

Is encoder

count==base

position?

No

Run Shoulder

motor

forward

Yes

Yes

Is encoder

count ==

shoulder

position?

No

Run Elbow

motor

backward

Is encoder

count ==

Elbow

position?

No

Run gripper

motor

backward

Is gripper

limit

switch==LOW

?

No

Call Place

homing

procedure

Figure 22: The place subroutine flow diagram

The place subroutine (see Figure 22) is called by the method set_arm_2 (x, y,z) which takes the

place positions as input and performs the inverse kinematics calculations on them. The place

subroutine is similar to the pick subroutine, with the only difference being the gripper

sequence. In the pick algorithm the gripper is opened before the home sequence is called by

the robot.


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4.5 Operation Description

4.5.1 Operation Sequence

1. Switch on the power and the robots moves to home position.

2. Press the start button.

3. The program prompts for user input.

4. The inverse kinematic procedure calculates the joint angles.

5. The robots moves to the pick position with the gripper open above the object to be

picked.

6. The robot picks the object and returns to the home position.

7. The robot moves to the place position.

8. The gripper opens and places the object.

9. The robot returns to the home position after placing is done.

10.The program waits for the operator to press the start button again to start another pick

and place task.

4.5.2 Safety

Extreme care should be taken while in the vicinity of the robot arm as the Scorbot robot

arm is very dangerous and carelessness can result in bad injuries.

1. Make sure the robots base is fastened to the work surface by means of at least three

bolts, set 120 apart .Otherwise, the robot could become unstable and topple over

during operation.

2. Make sure the robot arm has sufficient space in which to move freely.

3. Do not place your hands or fingers or any object within the robot arms operatingrange,

when the power supply is on.

4. When approaching or handling the robot, make sure the power supply switch on the

controller back panel is shut off, because an unexpected signal may cause the robot to

move.

5. Do not open the controller housing.

6. The workload should not exceed 1kg.

7. The operator should leave the robot at home position after using it, unless there is an

emergency which requires cutting power from the system.


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5 Design and Development Procedure

5.1 Introduction

This section of the document explains the procedure followed to attain the final design of the

project. The parameters used for selecting the power supply are also explained in this section.

The robot kinematics calculations are also explained in this section and the solution determines

the robot joint angle orientation for a given input of Cartesian coordinates. The robot motor

control method used for this project is also thoroughly covered.

5.2 Mechanical

5.1.2 Gear transmission mechanisms

The gears are already installed on the robot and were designed by Eshed Robotec and the main

purpose of this subsection is to explain the gear transmission calculations required for the

controlling of the robot. The gear transmission ratio is calculated for the shoulder and elbow to

determine the final resolution of the encoders which are installed directly on the DC motor

shaft. No calculation is done for the base and gripper because the information required to

conduct the gear ratio calculations is not supplied in the robots manual. This problem can be

overcome by finding the relationship between the angle rotated for the base and the number

of encoder counts required to reach that position. As for the gripper, control is achieved

through feedback information from the gripper limit switch and the force sensor. The gripper

stops opening when the gripper limit switch is hit and it stops closing when the required

gripping force is attained, thus the gripper control method does not require gear information.

Figure 23: Motor and encoder schematic


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The encoders are directly connected to the motor shaft (see Figure 23) so that the resolution is

reduced by a factor similar to the gear ratio. Suppose the gear box has a gear ratio Tm, if the

joint angle shaft rotates N times then the motor shaft rotates by:

With the encoderSuppose the encoder outputs Fpulses per revolution of the motor shaft, then the number of

pulses required to rotate the joint angle shaft by a single degree is proportional to:

The resolution is the reciprocal of the number of pulses required to move the output shaft by

one degree, thus:

Thus the resolution is improved by a factor equal to the gear ratio. This greatly increases the

number of encoder counts required to move the angle shaft per degree and thus improves the

accuracy of the robot. The SCORBOT ER III has three types of gear engines within the motors

case and each engine type has a different gear assembly mechanism. The engine types are:

Tm = 127.7: 1 - for the base, shoulder and elbow

Tm= 19.5: 1 - for the gripper


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5.1.2.1 Shoulder Transmission (Direct Transmission)

Figure 24: Shoulder double transmission

The shoulder uses a double transmission mechanism in which the shoulders armsare rotated

simultaneously by the shoulders motor. The torque is transmitted to the arms through a

hollow axle which is along the arrow labelled shoulder axle (see Figure 24). Both ends of the

axle are fixed, this helps in keeping the shoulder stable when subjected to a load.


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Figure 25: Base gear transmission (www.re positorio.bib.upct.es/dspace)

The small gear with Na= 18 teeth is installed directly on the servomotors output shaft and the

large gear with Nb= 72 teeth is fixed to the joint of the robots shoulder . Gear A and gear B

move in opposite directions. The motion chain formed by rotating the gear is:

- Transmission ratio of gear A to gear B

The transmission ratio also determines the relative rotational speeds between gear A and gear

B. In this situation, gear A rotates times faster than gear B.

- The speed of rotation of gear A - The speed of rotation of gear BSince the motor has its own gearbox, the total transmission ratio Tfrom the motor shaft to the

shoulder is: The value of the total transmission ratio is required for the encoder resolution of the shoulder.


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5.1.2.2 Elbow Transmission (Indirect Transmission between Gears)

The double transmission mechanism combination of the shoulder and elbow (see Figure 26)

prevents the arm from twisting and thus increases the stability of the arm.The axles of the

shoulder and elbow are fixed at their ends to the robot frame, this helps in preventing the

robot arm from twisting and thus increases stability.

Figure 26: Double transmission mechanism of shoulder and elbow


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The elbow works on a double indirect transmission mechanism (see Figure 27) with one double

indirect transmission mechanism for each side.

Figure 27: Indirect transmission between two stages (www.repositorio.bib.upct.es/dspace)

The transmission between gears A and B causes a change of rotation direction and the

transmission between gears C and D does not change direction because of the timing belt that

connects them. The number of teeth N for each of the gears is:

NA= 18

NB= 72

NC = 18

ND= 18

The transmission ratio T is a product of the relationships of all the gear stages and is calculated

as:

The relationship of the rpm speed between gear A and gear D is calculated as:

Taking the elbow motors gear ratio into consideration, the total transmission ratio Tfrom the

motor shaft is: This ratio is similar to the ratio calculated for the shoulder; this is due to the fact that thus

.Thus the gears connected by the belt have no effect on the gear ratio calculation results.


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5.1.2.3 Transmission of the base joint

The transmission of the base is a direct transmission mechanism. One gear is coupled to the

motor output shaft and rotates with the shaft and the driven gear is coupled to the rotor body.

The gear ratios were not supplied in the robot manual and no information could be gathered

from both the supplier and the Scorbot robot arms support group, thus no calculations aredone for the base. An alternative approach was therefore used to position the base which

involved calculating the number of pulse required to move the base by an angle of one degree.

5.1.2.4 Transmission of the gripper

The gripper fingers (see Figure 28) are moved by a smaller engine compared to other axes,

which is attached permanently to the wrists articulation. The gripper operates on a lead screw

mechanism, rotation of the gripper motor rotates the lead screw resulting in the opening or

closing of the gripper. The pitch of the lead screw determines the linear distance moved by the

gripper per revolution of the output shaft of the motor engine. Increasing the screw pitch,

results in an increase in speed of the gripper opening and closing, but however decreases the

resolution of the gripper fingers.

Figure 28: Gripper Transmission (www.repositorio.bib.upct.es/dspace)
http://www.repositorio.bib.upct.es/dspacehttp://www.repositorio.bib.upct.es/dspace


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5.2 Electrical

5.2.1 Encoder Circuit Design

Figure 29: Encoder circuit

According to Eshed Robotec (1995: F-2), the emitting diodes are fed by a 5V power supply and a

39 resistor in series. The resistor is however not included in the encoder (Figure 29 shows thefinal circuit with resistors added). The encoder also has two open collector outputs. Therefore

the main purpose of the electrical design is to add a current limiting resistor for the LEDs in

series and design a circuit to interface the collector outputs to the Arduino.


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Figure 30: LED circuit calculations diagram

The value of the rated minimum current of the LEDs can be approximated since the supply

voltage and the resistor required is specified by the manufacturer. The following parameters

are used for the calculations:

R = 39 Ohms

VCC = 5V

The voltages of the LEDs can be considered to be zero. This has an effect of reducing the

calculated current from the actual current. The value of the calculated current can be used for

further calculations since it will be below the rated current. The following calculation is used to

approximate the current required by the diodes:

Thus to prevent the diodes from blowing up, a resistor should be selected such that the current

in the diode circuit is below 0.128A.A resistance of 100was selected because it was readily

available.


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The following calculation is done to verify that the limiting current is not exceeded:

The resulting current is below the limiting current and thus a 100 Ohm resistor can be used.

Figure 31: Phototransistor resistance calculation

The phototransistor (see Figure 31) behaves like a switch. Its terminals open when exposed to

light and the terminals are closed when it is not exposed to light. The output pin of the

phototransistor is interfaced with the MCU through a pull-up resistor. The pull-up resistor

chosen should satisfy these conditions (Ronzo, 2012):

1. When the button is pressed, the input pin is pulled low. The value of the resistor

controls how much current you want to flow from 5V through the resistor R1, through

the button, and then to ground.

2. When the button is not pressed, the input pin is pulled high. The value of the pull -up

resistor controls the voltage on the input pin.


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The general rule for condition 2 is to use a pull-up resistor (R1) shown in Figure 31 that is an

order of magnitude (1/10th) less than the input impedance (R2) of the input pin (Ronzo,

2012).The maximum current allowed for the arduino IO pins is 40mA and these pins have an

input impedance which varies from 100k-1M.The Arduino Mega detects a voltage as high if

it is 3V or more, thus the selected resistor should pull-up the voltage to at least 3V.Thereforewith these guidelines R1 can be calculated as:

There is need to verify the amount of current drawn by the 10k resistor and this is calculated

using ohms law as:

The calculated current is less than 40mA and it is below the maximum allowable current and

thus the selected resistance value can be used. The voltage on the input pin of the MCU when

this selected resistor is used is:

This value can be detected as a high input by the MCU since it is greater than 3V.A 10k

resistor satisfies the selection parameters and was implemented in the circuit.

The next phase involved implementing the resistor circuit on a breadboard. The circuit was

tested on an oscilloscope to verify if the correct pulses were being generated as the motor was

being run. Finally the circuit was soldered for all the four axes and its performance was tested

on an oscilloscope. The resulting pulses were perfect, fluctuating from roughly 0V -5V as

required. The pulses for the two channels had a 90 degrees phase shift as expected (see Figure

32).The pictures of the experimental setup are in Appendix C-1.


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Figure 32: Encoder output as seen from oscilloscope

5.2.2 Limit switch and Pushbutton circuit design

Figure 33: Limit switch pull-up resistance selection

The switches and pushbuttons are implemented with a stand pull-up resistance of R1=10k.

The switch output to the MCU is pulled up to 5V when the switch is open and is pulled to


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ground when the switch is closed. The calculation to verify the selection of the pull-up resistor

is similar to the calculation done for the phototransistor. The only difference between the two

circuits is that the phototransistor in Figure 31 is replaced by a switch in Figure 33.The circuit

performance was analysed in Multisim and the digital multimeter readings gave the expected

results (see Figure 34). The open switch gave an output voltage of approximately 5V while theclosed switch exhibited zero voltage output.

Figure 34: Multisim simulation of the pull-up switch circuit

The circuit for all switches was soldered on a veroboard and was tested by read it through a

digital input pin on the Arduino MCU. The results were displayed on the serial monitor, which is

a HyperTerminal. An output of logic zero was observed when the switches were closed and a

logic one was observed when the switches were open (see Figure 35).


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Figure 35: Switch test results displayed through the Arduino serial monitor

5.2.3 Force Sensor Circuit design

Figure 36: Recommended circuit of the force sensor (Interlink, 2012: 18)

Figure 36 shows the suggested electrical interface of Force sensing resistors according to

Interlink (2012: 18).The output voltage (VOUT) and the input force variation for different

voltage divider resistance values (RM) is shown in figure 37.The curve is plotted for an input

force which varies between 0-1kg.


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Figure 37: Force vs Voltage characteristic for the A401 sensor

The value of 100k was chosen for the voltage divider circuit. This value was chosen because

the load which was being picked by the robot had a mass of 170g.The 100k resistor has the

largest output voltage range which stretches from 0V-5V and it also has the most sensitive to

changes in the force values in the 0g-200g domain. The output voltage is calculated using the

voltage divider equation.

Voutis connected to the analog pin of the Arduino MCU.The Analog to Digital Converter (ADC)

which is a peripheral device on the Arduino MCU converts the voltage value from the analog

pin to a value that can be interpreted by the MCU.The Arduino MCU has a 10bit ADC which

corresponds to a range of:

This range corresponds to values between 0-1023.The ADC value on an Arduino which is a 5V

system, is calculated as:


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5.2.4 Power Supply unit selection

The equation is used to calculate the total power required by the motors; the otherelectrical circuit components require a 5V supply and are powered by the Arduino MCU which

has its own 5V power supply. The parameters used to select the power supply are:

The motor voltage requirements = 5V DC

The motor maximum current = 2A

The number of motors which require power is four and a worst case scenario in which all the

motors run at once is used to calculate the total power. In practice, such a case will never

happen since the motors run sequentially one after the other. The total amount of power and

current required from the power supply, in a worst case scenario, is:

Thus, the minimum power supply power required for running the motors is 96W and the total

current drawn is 8A. Power supplies from various suppliers were considered (see Table 3).

Table 3: Power supplies considered

Manufacturer Specifications Supplier Cost

Mean Well 230V ac to 12V dc

18 A

Second hand

shop

R 100

RS 230V ac to 12V dc

18 A

RS components R672.95

Hobbytronics 230V ac to 24V dc

10 A

Electronics 123 R132.95

The Mean Well power supply which had the cheapest price, but still retained the required

functionality, was chosen.

5.3 Robot Kinematics

5.3.1 Denavit Hartenberg Forward and Inverse Kinematics

The inverse kinematics technique is used to calculate the joint angle parameters for a given end

effector orientation. The pick and place positions of the robot gripper are described in terms of

a fixed Cartesian coordinate system. Therefore the main purpose of this technique is to map

the Cartesian coordinates of the gripper through a function which outputs the angles to which

the joints of the robot arm must be rotated. The coordinate frame assignment of the Scorbot


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robot arm with respect to the D-H rules is depicted in Figure 38(Deshpande & George, 2012:

479).

Figure 38: The Denavit-Hartenberg frame assignment of the Scorbot ER-III (Deshpande & George, 2012:479)

The reference frames are assigned according to the following rules (Spong et al, 2007:70):

The -axis is orthogonal to the axes and .

The -axis also intersects the and axes.

The intersection point of and marks the origin of joint .

can be found using the right hand rule of Cartesian coordinates.

The transformation is described by the DH parameters:

: offset along previous to the common normal.

: angle about previous , from old to new .

: Length of the common normal.

: Angle about common normal, from old axis to new axis.


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The D-H parameters are represented in a table (see Table 4) assigning the specific

parameters for the Scorbot ER-III.The parameters are substituted in to the D-H matrices

which the end effector position for a given robot arm orientation. In other words, the

transformation is a forward kinematics function. The forward kinematics solution results in

a set of equations, which express the end effectors Cartesian coordinates in terms of the D-H parameters. The Inverse kinematics involves solving the equations so that the joint angles

can be calculated.

Table 4: Scorbot ER-III D-H parameters

The transformation matrix from joint i to joint i+1 is shown in Figure 39.

Figure 39: Scorbot transformation matrix (Deshpande& George, 2012: 479)

And Si=sin i, Ci= cos i, Si=sin i, Ci=cos i, Sijk=sin (i+ j+ k), Cijk=sin (i+ j+ k)

Multiplying alli-1

Tifor i = 1 to 5 (0T1,

1T2,

2T3,

3T4,

4T5), results in the total transformation from

0

T5.The total transformation matrix is shown in Figure 39.


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Figure 40: The total transformation matrix (Deshpande & George, 2012: 479)

The end effector transformation matrix (Te) is expressed as:

Figure 41: The end effector transformation matrix (Deshpande & George, 2012: 479)

For the Inverse kinematics problem, the end effector position is known and therefore the all the

entries of Te are known. The inverse kinematics problem is basically the solution to theequation:

0T5= Te

This results in the following system of equations shown in Figure 42:

Figure 42: Inverse kinematics equations (Deshpande & George, 2012:479)


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This set of equations is not easy to solve and therefore a geometric solution to the problem is

followed to determine the angle parameters for the robot arm.

5.3.2 Geometric approach to inverse kinematics

Figure 43: Robot representation for geometric analysis

Figure 43 shows the robot arm and the Cartesian frame (i.e. the xyz frame) from which the pick and

place positions are measured from. In Figure 44 and Figure 45 the robot arm is removed so that the

shapes used for the geometric calculations are easy to view.There are two scenarios presented by

the geometric approach, let:


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For s > 0 (i.e. the wrist joint is higher than the shoulder joint along the Z-axis), the equation of

the geometric problem is derived as:

Figure 44: Inverse kinematics geometric approach

The elbow angle is calculated by applying the cosine rule to the triangle ABC, thus:


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From the definition of the sine rule, angles A and B can be calculated as:

Therefore:

For the second scenario s < 0, the orientation of the triangle ABC (see Figure 45) is changed and

it only affects the solution for due to the change in position of angle d. In this end effectororientation, the wrist joint is lower than the shoulder joint along the positive Z-axis.

Figure 45: Geometric approach for the second scenario

For this orientation, the value of becomes: ( )


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Either formula can be used for the scenario in which S = 0. On analysis of the movement of the

Scorbot robot arm, it is observed that the robots ulna moves horizontally when the humerus is

in motion. The motion of the ulna is always along the direction of E (see Figure 46).Thus, the

elbow joint angle is always changing whenever the shoulder is in motion. Thus, for motion

control the value calculated for will not be the actual angle the ulna has to be rotated.

Figure 46: Ulna motion for the Scorbot robot arm

The final position of the ulna is from the humerus axis (see Figure 46). After the movementof the humerus about the shoulder angle, the ulna will have moved an angle of a. Therefore,

for position control, the controller should send commands to move the elbow joint by an angle

of where angle ais given by:

5.3.4 Sample calculations

Suppose it is required to move the end effector to the point the jointangle parameters are calculated by the MCU as:

Therefore the second scenario of the inverse kinematics problem should be solved.

=


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( ) ( ) ( )

Thus the inverse kinematics function maps the point to .From the elbow joint motion trajectory analysed, itis required that the control algorithm should only move the joint by: The base and shoulder are rotated by and respectively to attain the desired end effectorposition for the pick and place tasks.

5.4 Position Control of the robot arm

5.4.1 Position Control System

Figure 47: Joint control system block

The position control system applied in this project is illustrated in Figure 47.The solution from

the inverse kinematics is converted into pulses through calculations which will described later.


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The number of pulses required to reach a certain angle is stored as a variable for the desired

position. The MCU drives the joint motor and the encoder count is monitored while the motor

is running. The joint motor is driven until the difference between the encoder count and the

number of pulses required to reach the position is zero. The MCU sends commands to the H-

Bridge driver to stop the motor when the difference is zero.

5.4.2 Optical Encoder decoding

Figure 48: Output pulses for channels A and B (National Instruments, 2001)

The optical encoder of the Scorbot robot arm outputs two pulses positioned 90 degrees out of

phase (see Figure 48).These two channels show both the position and direction in which the

joint motors rotate. For example if A leads B then the motor is rotating in a clockwise direction

and if B leads A, then the motor is rotating in an anti-clockwise direction. The position can be

monitored by counting the number of pulses and the direction can be monitored by checking

the relative phase of channels A and B.

Figure 49: X1 decoding scheme (National Instruments: 2001)

The X1 decoding scheme (see Figure 49) is used to control the position of the joint angles of the

robot arm. Angular position is determined by the number of falling or rising edges counted by


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the MCU in order to attain that angle. The sequence 765(see figure 49) in which channel B leads

channel A was used to determine the number of counts required to reach a position. The MCU

uses an interrupt to on every falling edge of A and checks B to detect the direction of rotation.

If Ch B is high on the falling edge of Ch A, the count is incremented and if B is low the count is

decremented. The count is incremented until the desired number of pulses required is reached.

The Inverse kinematics procedure calculates the joint angle parameters for a given angular

position. For the position control of the robot arm, the algorithm implemented takes the angle

as input and calculates the number of pulses required to rotate to that given angle. The formula

implemented to calculate the number of pulses required to move one degree is:

Where:

Number of pulses required to move by one degree

Encoding type, which is 1 because X1 decoding is used for controlling all the joint motors. Number of pulses generated per shaft revolution (which is equal to 6 for all joints exceptthe gripper)

Gear transmission ratio from the motor driving gear to the joints driven gear.5.4.4 Calibration Procedure

Due to the fact that measurements taken in labs are not precise, there is need to take multiple

measurements of the dependent variable at every value of the independent variable. A

calibration procedure was done so that the relationship between the number of encoder

counts required to reach a certain angle can be expressed as a function of the desired output

angle. The number of pulses is the independent variable(y) that was manipulated and the

measured angle was the dependant variable(x) that was recorded for each joint.

For each pulse value three angle recordings were taken, the mean value of these readings was

calculated and this mean value was plotted as a single point on the calibration curve. The mean

value was calculated using the AVERAGEfunction in using Microsoft Excel and it is equal to:

The standard error was used to express the uncertainty of the calculated mean values of the

angles which are used to plot the calibration curve.


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The standard error is calculated from the standard deviation as:

The standard error represents the confidence range in which the mean value represents the

true value of the measured angle. The standard error is expressed visually through errors bars

which are shown in the calibration curves (see Figure 51).A wide error bar represents a low

level of confidence in the representation of the true value by the mean value(Labwrite,2012).

The linear regression method is used to express the number of pulses as a linear function of the

angle required to move the joint. The linear function is of the form:

Where M is the gradient of the resulting curve, and c is the y-intercept. The mean values for

each recording were used to plot the calibration curve.


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5.4.4 Base Position Control

5.4.4.1 Base Calibration

Figure 50: Base rotation

The base control is achieved through a calibration process which was conducted at 60% duty

cycle because the experimental results (see section 6.1) showed that the base had the least

error when the base motor was driven by a PWM signal with 60% duty cycle. The methodology

used involved keeping the numbers of pulses sent to the MCU as the independent variable.

Calibration was done at 100 pulse intervals for both clockwise and anticlockwise rotation of thebase since the base is controlled from the center. The actual angles moved by the base were

measured using a protractor. The calibration procedure was the only method implemented for

the control of the base because no information relating to the gear mechanism was found. The

table of results can be found in Appendix C-2.Figure 37 shows the results for the clockwise

calibration.


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Figure 51: Base clockwise rotation calibration curve

The calibration was modelled as a linear pattern. The results had a great correlation coefficient

of 0.9945; this value is close to 1 which indicates that the recorded data closely resembles a

linear model. The maximum standard error recorded is +/- 3.4 degrees which corresponds to1000 pulses this can be seen visually by the widest error bar at 1000 pulses(see Figure 51). The

resulting equation was solved forxwhich represents the number of pulses.

From the inverse kinematics sample calculations, to move the base 26.565 degrees towards the

positive y direction, the number of pulses required is:


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The results of the base anticlockwise calibration showed a good correlation coefficient of 0.992,

this value is close to 1 which indicates that the recorded data closely resembles a linear model.

The maximum standard error recorded

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