Universität zu Lübeck Institut für Technische Informatik Erik Maehle University of Lübeck...

UniversitätUniversitätzu Lübeckzu Lübeck

Institut fürInstitut fürTechnische InformatikTechnische Informatik

Erik MaehleErik MaehleErik MaehleErik Maehle

University of LübeckUniversity of Lübeck

Institute of Computer EngineeringInstitute of Computer Engineering

Ratzeburger Allee 160Ratzeburger Allee 160

D-23538 LübeckD-23538 Lübeck

E-Mail: [email protected]: [email protected]

University of LübeckUniversity of Lübeck

Institute of Computer EngineeringInstitute of Computer Engineering

Ratzeburger Allee 160Ratzeburger Allee 160

D-23538 LübeckD-23538 Lübeck

E-Mail: [email protected]: [email protected]

The Organic Robot Control Architecture ORCA and Its The Organic Robot Control Architecture ORCA and Its Application to the Fault-Tolerant Walking Machine OSCARApplication to the Fault-Tolerant Walking Machine OSCAR **

The Organic Robot Control Architecture ORCA and Its The Organic Robot Control Architecture ORCA and Its Application to the Fault-Tolerant Walking Machine OSCARApplication to the Fault-Tolerant Walking Machine OSCAR **

Seminar ‚Organic Computing‘, Dagstuhl, March 31 – April 4, 2008Seminar ‚Organic Computing‘, Dagstuhl, March 31 – April 4, 2008Seminar ‚Organic Computing‘, Dagstuhl, March 31 – April 4, 2008Seminar ‚Organic Computing‘, Dagstuhl, March 31 – April 4, 2008

Supported by DFG under MA1412/7-1, associated to DFG SPP 1183 ‚Organic Computing‘Joint Project with University of Osnabrück and Fraunhofer AIS



Motivation

Autonomous mobile robots in human environments

-> unstructured, -> complex control

dynamically changing systems

environment

-> no explicit model -> no explicit fault

of the environment model

fault-tolerance, safety engineering bottleneck



Organic Systems

Organic systems adapt dynamically to environment and malfunctions

- uncertainties

- unknown environment

- unforeseen situations

Our approach: controlled self-organization

Inspiration: autonomic nervous system and immune system

Aim: - detect, react, and adapt to malfunctions

- avoid critical system states at any time

- low cost implementation and engineering



•Introduction

•ORCA Architecture

•Walking Robot OSCAR

•Self-Organizing Walking

•Conclusion

Overview



ORCA - Organic Robot Control Architecture

Reflexes

Motor (PWM)

Motor-Controller

Motors (PWM)

Perception Proprioception Motor-Controllers

Reflexes

Behaviours

Planning

Gait-Pattern-Gen.Gait-Pattern-Gen.Gait-Generation /-Selection

Gait-Pattern-Gen.Gait-Pattern-Gen.Sensor Modules

decisionallevel

functionallevel

hardwarelevel

OCU

OCUs

BCU = Basic Control Unit

OCU = Organic Control Unit



OCU-Architecture

- Monitor: anomaly detection

- Memory: short term history

- Reasoner: hard real-time determination of a counteraction

Monitor Reasoner

Memory

Variant of Observer/Controller Architecture



Methodological Approaches

- Signals reflecting the ´health´ of a signal or a BCU

e.g. - noisiness, confidence of output results,

- load state; error state

- Adaptive action selection

IF movement=blocked

THEN activation of commanded behaviour -=5%,

activation of non-commanded behaviour +=5%

- Learning to treat malfunctions

=> Learning at OCU-level



OSCAR - Organic Self-Configuring and Adapting Robot

Hexapod with 18 DOF (Servos)

Ground contact Sensor:Simple switch per leg

Control Computer:- JControl/Smartdisplay- Servo Driver Modul- I2C-Bus

Programming Language:JAVA



Basic Approaches for Autonomic Walking

Stick Insect (Carausius morosus) Leg and Joints

AEP: Anterior Extreme PositionPEP: Posterior Exreme Position

Swing Phase

Stance Phase

3 DOF

Modelled by WALKNET[Cruse et al. Uni Bielefeld]



Distributed Walking Control in OSCAR

Swing phase has constant length.

Duration of stance phase determines velocity.

Slightly different leg orientation depending on leg position (F, M, L).

So far only one single rule implementedwith circular neighborhood relation for all legs.

Single local rule for each leg[i]:



Self-Organizing Gait Patterns in OSCAR

Slow GaitSlow Gait Tetrapod GaitTetrapod Gait Tripod GaitTripod Gait

Emergent Gait Emergent Gait Patterns with Patterns with

Increasing Speed!Increasing Speed!



Insect Walking with Lost Legs

[Source: Holk Cruse, Uni Bielefeld]



Leg Coordination After Leg Loss for OSCAR

Same single rule, onlyneighborhood relation

changes.



OSCAR Walking with Lost Middle Legs

Simulated Amputation



ORCA Organic Robotic Control Architecture



Curve Walking Towards a Goal



Curve Walking with Lost Leg

a m p uta tio n e

All 6 legs intact

Left leg lost

Right leg lost



Conclusion

ORCA – Organic Robot Control Architecture

- BCUs (Basic Control Units) for functional control

- OCUs (Organic Control Units) for monitoring, fault adaption and optimization

- Learning based on hybrid crisp fuzzy methods and adaptive filters

OSCAR - Organic Self-Configuring and Adapting Robot

- Self-organizing gait patterns inspired by insects

- Monitoring of leg health status by sensor signals from joints and feet

- Self-organizing gait patterns also in case of lost legs



Current Work

- Tools for hybrid crisp fuzzy methods (U Osnabrück)

- Integration of learning methods into ORCA/OSCAR

- New hardware platform for OSCAR (2 * ARM9 + 6 * ATmega32)

- Additional sensors (inertial, ultrasonic, laser, inclinometer, camera, .. )

- Tolerance of less severe leg faults than complete leg losses

- More sophisticated methods of anamoly detection (e. g. information theory, fuzzy)

- Combination with obstacle avoidance in more challenging environments

- Application of ORCA to other robot platforms (e .g. fish-like underwater robots)

Acknowledgement of contributions of ORCA Group MembersWerner Brockmann (U Osnabrück), Adam El-Sayed-Auf, Karl-Erwin-Grosspietsch(Fraunhofer AIS), Bojan Jakimovski, Marek Litza, Florian Mösch

Universität zu Lübeck Institut für Technische Informatik Erik Maehle University of Lübeck...

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