Evolvability of Robots

8/11/2019 Evolvability of Robots

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Prepared ByNirav Thakkar

Ajit Pawar


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Overview Introduction

Advantages

EvolutionAdaptation

Conclusion


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Introduction European project SYMBRION, dealing with self-

assembling of swarm of robots

Symbiotic Evolutionary Robot Organisms Commencement - February 2008

Funded by European Commission within program

Future and Emergent Technologies

SYMBRION taken from biological term symbiosis

Based on bio-inspired approaches and computational

paradigms


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Intro(cont ) Symbiosis represents the biological inspiration for the

further development of robotic systems

Symbiotic robotics

Each robot of the swarm is able to run as an individual orbe aggregated in an organism

The robots should be able to re-program themselves andadapt to varying environments


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Advantages In a swarm of robots the individual entities can profit

from cooperation, emerge new behaviors and can

increase the overall fitness

In a more advanced approach, robots work not only

collectively, but can also aggregate into multi-robot

organisms and can share energy, resources and

functionality

eg. when there is a large obstacle like gap or wall, which

robots cannot pass, so idea is that robots can aggregate

into larger artificial organisms and pass this obstacle


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Being equipped with adocking mechanism, therobots can autonomously

aggregate or disaggregate

Once the robots have beenconnected to each other,they are able to share

resources such ascomputational power orenergy over a common bussystem


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Aggregated organism can be treated as a large,distributed network

In order to achieve evolve-ability on hardware andsoftware level the robots have to be able tocommunicate over CAN-bus or ZigBee and share theirresources within the organism


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Evolution Robots are placed randomly in the arena and interact withone another whenever they come into communicationrange of the infrared equipment (about 6 cm)

Each robot signals its status via an infrared broadcast,which is emitted frequently (about 100 times per second)

Thus, robots can virtually perceive other robots despitetheir marginal sensory capabilities by reading theirbroadcasts.

The maximum lifetime is set to 100 seconds, which isenough to keep the population from going extinct andleads to a large number of generations in the one hour runtime of the robots


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Individuals die if their energy runs out and anotherfertilized robot may then implant its energy

The robot is selected depending on the energy levels aswell as the distance between the robots

The dead individual remains open for implantation fora certain period, after which the egg with the highestdowry is used to reprogram the controller


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Evolution(cont) Each robot wanders around the environment -forward

movement

Each robot has an internal energy level

full at birth and linearly decreases over time

Once energy is depleted, the robot is considered deadand is free for insemination by another robot

As a consequence, the amount of energy the robot iswilling to invest to win a bidding process forinseminating dead robots directly impacts thereproduction ability of the individual.


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Evolution(cont) Therefore we transfer biological principles to the robot

platform

As a result, new genes with new functionality can appear,which can increase the fitness of an individual or of the

whole organism

By studying the genome structures and the evolutionary

process we should be able to deduce general principles ofevolution


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Adaptation Different levels of adaptation

Should be able to adapt on s/w as well as on mechanicaland electronics part

Mechanical evolve-ability

Mechanical -> Once made hard to change

So build small module that can organize into large

organisms No evolve-ability on separate modules

However organism can change its own morphology and itsfunctionality


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Evolve-ability of Electronics part

Small modules wired to a common electronics sys

Depending on the role of swarm members, one or morePCBs implemented

PCBs

Core

Shadow


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Core PCB ARM Cortex M3 Takes care of locomotion, sensing etc

RTOS: ensures real time ability

Shadow PCB Xscale mp SoC: allows direct interface to camera, laser scanner, sensors

and actuators Embedded Linux with 600MHz freq Covers tasks like strategy calculation and selection,

adaptation and trajectory planning Sleep mode to save power


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Comm. between different main boards withinorganism is possible through docking

Docking allows wired connection of CAN bus Common power bus


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Adaptive software framework Robots can be treated as

Stand-alone units

Swarm Organism

Swarm of organism

Each state of aggregation have diff requirements

s/w has to be extendable and modular A common genome structure and interfaces for learning

have to be implemented


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Role of s/w framework is to abstract functions of lowerlevel to higher level

Robot runtime system has to band both processors to

coordinate in order to divide workload Robot runtime system provides basic comm channels

like ZigBee or CAN and controls power consumption

RTOS will take care of basic operations

Middleware support


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High-level controller

Middleware

Robot1

Core Shadow

Robot2

Core Shadow


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High-Level Controller Runs on robot and has internal and external stimuli as

inputs

Can change internal states

Can trigger o/p like sensors and actuators Sensor fusion module

Data from fusion module sent for learning

Learning engine integrates new functions based onprocessed data in fusion module

Genome maps the controller behavior into inheritableinfo


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References Florian Schlachter, Eugen Meister, Serge Kernbach and Paul Levi Evolve-ability of

the robot platform in the Symbrion project 2008 IEEE

Guy Baele, Nicolas Bredeche, Evert Haasdijk, Steven Maere, Nico Michiels Open-ended On-board Evolutionary Robotics for Robot Swarms 2009 IEEE


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THANK YOU

Evolvability of Robots

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