© Rolf Pfeifer

VISIONTRAIN Thematic School

Morphological computationConnecting brain, body and environment

Les Houches, 9-14 March 2008

Rolf PfeiferArtificial Intelligence Laboratory, Department of Informatics

University of Zurich, Switzerland

© Rolf Pfeifer

Lecture 2

Design principles for intelligent systems

© Rolf Pfeifer

Contents Lecture 2

• real worlds and virtual worlds• properties of complete agents• the quadruped „Puppy“ as a complex dynamical

system• illustration of selected design principles• summary

© Rolf Pfeifer

Contents Lecture 2

• real worlds and virtual worlds• properties of complete agents• the quadruped „Puppy“ as a complex dynamical

system• illustration of selected design principles• summary

© Rolf Pfeifer

Real worlds and virtual worlds

differences?

© Rolf Pfeifer

Real worlds and virtual worlds

differences?

chess vs. soccer

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Real worlds and virtual worlds

• information acquisition takes time• limited information• noise• no clearly defined states• agents must do several things• own dynamics, time pressure• limited predictability, non-linear, sensitivity to

initial conditions

bounded rationality

© Rolf Pfeifer

Contents Lecture 2

• real worlds and virtual worlds• properties of complete agents• the quadruped „Puppy“ as a complex dynamical

system• illustration of selected design principles• summary

© Rolf Pfeifer

Properties of complete agents

• subject to the laws of physics• generation sensory stimulation• affect the environment through behavior• complex dynamical systems• perform morphological computation

© Rolf Pfeifer

Contents Lecture 2

• real worlds and virtual worlds• properties of complete agents• the quadruped „Puppy“ as a complex dynamical

system• illustration of selected design principles• summary

© Rolf Pfeifer

Rapid locomotion and “cheap design”

• hard problem

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Rapid locomotionthe quadruped “Puppy”

Design and construction:Fumiya Iida

rapid locomotionin biological systems

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The quadruped “Puppy”: summary

• simple control (!)• no sensors• spring-like material properties• self-stabilization

Design and construction:Fumiya Iida

© Rolf Pfeifer

The quadruped “Puppy”: summary

• simple control (!)• no sensors• spring-like material properties• self-stabilization

Design and construction:Fumiya Iida

principle of “cheap design”

© Rolf Pfeifer

The “mini dog” by Fumiya Iida

Artificial Intelligence LaboratoryDept. of Information TechnologyUniversity of Zurich

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The quadruped “Puppy”: summary

• simple control (!)• no sensors• spring-like material properties• self-stabilization

Design and construction:Fumiya Iida

© Rolf Pfeifer

“Puppy” on the treadmill

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Video from high-speed camera –self-stabilization

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Video from high-speed camera –self-stabilization

- no sensors- no control

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Self-stabilization

• “computation” performed by physical dynamics of agent basin of attraction

• stabilization through mechanical feedback• “intra-attractor dynamics” (Kuniyoshi)

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Implications of embodiment

Pfeifer et al., Science,16 Nov. 2007)

© Rolf Pfeifer

Implications of embodiment – self-stabilization

Pfeifer et al., Science,16 Nov. 2007)

“Puppy”

© Rolf Pfeifer

LH

LF

RF

RH

100 200 300 400 500 600 700 800 9000 t (ms)1000 1100 1200 1300

LH

LF

RF

RH

100 ms

LH

LF

RF

RH

1400

gait patterns

Fast gallop

Moderatewalking

Fast runningtrot

© Rolf Pfeifer

Gait patterns as attractor states

Illustration by Shun Iwasawa

induced through interactionwith environment

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Morphological computation

Figure 4.1Morphological computation. (a) Sprawl robot exploiting the material properties of its legs for rapid locomotion. The elasticity in the linear joint provided by the air pressure system allows for automatic adaptivity of locomotion over uneven ground, thus reducing the need for computation. (b) An animal exploiting the material properties of its legs (the elasticity of its muscle-tendon system) thus also reducing computation. (c) A robot built from stiff materials must apply complex control to adjust to uneven ground and will therefore be very slow.

© Rolf Pfeifer

Fore legs: iiii BtAP 111 )sin(

Hind legs: iiiii BtAP 222 )sin(

(Iida, Gomez and Pfeifer, 2005)

Gait 1

Gait 0

Gait patterns for grounding a body image

© Rolf Pfeifer

Contents Lecture 2

• real worlds and virtual worlds• properties of complete agents• the quadruped „Puppy“ as a complex dynamical

system• illustration of selected design principles• summary

© Rolf Pfeifer

Time-scales and design principles

Design principles

collective intelligence

© Rolf Pfeifer

Agent design principles

Name Description

Three constituents Ecological niche (environment), tasks and agent must always be taken into account

Complete agents Complete agent must be taken into account, not only isolated components

Parallel, loosely coupled processes

Parallel, asynchronous, partly autonomous processes, largely coupled through interaction with environment

Sensory-motor coordination

Behavior sensory-motor coordinated with respect to target, self-generated sensory stimulation

Cheap design Exploitation of niche and interaction; parsimony

Redundancy Partial overlap of functionality based on different physical processes

Ecological balance Balance in complexity of sensory, motor, and neural systems; task dsitribution between morphology, materials, control, and interaction with environment

Value Driving forces: developmental mechanisms; self-organization

© Rolf Pfeifer

The Three-Constituents Principle

• ecological niche• desired behaviors and tasks• design of agent itself

scaffolding

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Complete Agent Principle

When designing an agent, always thank about complete agent behaving in real world.

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Regonizing andobject in acluttered environment

illustration byShun Iwasawa

manipulation of environment facilitates

perception

robot experimentsby Giorgio Metta

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Regonizing andobject in acluttered environment

illustration byShun Iwasawa

manipulation of environment facilitates

perception

complete agent principle

principle ofinformation self-strcuturing

© Rolf Pfeifer

Principle of “cheap design”

Exploitation of

- ecological niche

- characteristics of interaction with environment

design easier: “cheap”

Example:• Lecture 1: “Swiss robots”

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The “Passive Dynamic Walker”

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Humanlocomotion

Qrio (Sony) Asimo (Honda)

Denise(Delft)

Passive Dynamic Walker(Cornell)

CornellMITDelft

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“Passive Dynamic Walker” – the brainless robot (1)

walking without controlDesign and construction:Ruina/Wisse/Collins, Cornell University

Morphology:- shape of feet- counterswing

of arms- friction on

bottom of feet

© Rolf Pfeifer

“Passive Dynamic Walker” – the brainless robot (2)

walking without control

Morphology:- shape of feet- counterswing

of arms- friction on

bottom of feet

Design and construction:Ruina/Wisse/Collins, Cornell University

self-stabilization

principle of “cheap design”

© Rolf Pfeifer

Implications of embodiment

Pfeifer et al., Science,16 Nov. 2007)

© Rolf Pfeifer

Implications of embodiment – self-stabilization

Pfeifer et al., Science,16 Nov. 2007)

passive dynamic walker

© Rolf Pfeifer

Where is the memory for walking?

© Rolf Pfeifer

Extending the “Passive Dynamic Walker” – the almost brainless robot

Design and construction:Ruina/Wisse/Collins, Cornell University

Collins, Ruina,Tedrake

“Denise”Martijn Wisse

Morphology:- shape of feet- counterswing

of arms- friction on

bottom of feet

© Rolf Pfeifer

Extending the “Passive Dynamic Walker” – the almost brainless robot

walking with little controlDesign and construction:Martijn Wisse, Delft University

Morphology:- wide feet- counterswing of arms- friction on bottom of feet- high energy efficiency

self-stabilization

© Rolf Pfeifer

Pneuman: passive dynamic walker(with pneumatic actuators and torso)

design andconstruction:Koh Hosoda, OsakaUniversity

only hip-joint actuatedothers: passive but pre-pressured (closed valves)

self-stabilization

© Rolf Pfeifer

Implications of embodiment – self-stabilization

(Pfeifer et al., Science,16 Nov. 2007)

Denise (Wisse)Pneuman (Hosoda)

© Rolf Pfeifer

Famous robots:Asimo, Qrio, H-7, HOAP-2, HRP-2

H-7 (Univ. of Tokyo)

HRP-2 (Kawada) Qrio (Sony)

HOAP-2 (Fujitsu)

Asimo (Honda)

© Rolf Pfeifer

Famous robots:Asimo, Qrio, H-7, HOAP-2, HRP-2

H-7 (Univ. of Tokyo)

HRP-2 (Kawada) Qrio (Sony)

HOAP-2 (Fujitsu)

Asimo (Honda)

© Rolf Pfeifer

Famous robots:Asimo, Qrio, H-7, HOAP-2, HRP-2

H-7 (Univ. of Tokyo)

HRP-2 (Kawada) Qrio (Sony)

HOAP-2 (Fujitsu)

Asimo (Honda)

no exploitation of dynamics, morphology,and materials

© Rolf Pfeifer

Biped walking:Exploiting interaction with environment

• leg as pendulum• control for free• energy efficiency• self-stabilization

principle of “cheap design”

© Rolf Pfeifer

“Cheap” diverse movement and locomotion

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Case study on morphology and materials: “Stumpy”

Design and construction: Raja Dravid, Fumiya Iida, Max Lungarella, Chandana Paul

actuated joints

almost brainless (very simple control)two motors

elastic materials

surface properties

© Rolf Pfeifer

“Cheap” behavioral diversity: “Stumpy”

Design and construction: Raja Dravid, Fumiya Iida, Max Lungarella, Chandana Paul

© Rolf Pfeifer

“Stumpy”: Summary

• Exploitation of dynamics– natural stiffness and elasticity of the materials– surface properties of the feet

• many behaviors with only two joints• self-stabilization• good control through exploitation of morphology and

materials little control required

principle of “cheap design”

© Rolf Pfeifer

Implications of embodiment – self-stabilization

(Pfeifer et al., Science,16 Nov. 2007)

Denise (Wisse)Pneuman (Hosoda)Stumpy (Dravid/Iida)

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Stumpy - history

design and construction:Raja Dravid, Fumiya Iida and Chandana Paul

© Rolf Pfeifer

Exploitation of system-environment interaction for control: ants and fish

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Insect walking

Holk Cruse• no central controller for leg-

coordination• only local communication

neuronalconnections

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Insect walking

Holk Cruse• no central controller for leg-

coordination• only local communication

neuronalconnections

© Rolf Pfeifer

Insect walking

Holk Cruse• no central controller for leg-

coordination• only local communication• global communication

through interaction with environment

neuronalconnections

© Rolf Pfeifer

Global communication through interaction with environment

angle sensorsin joints

exploitation of interaction with environmentsimpler neuronal circuits

“cheap design”

“parallel, loosely coupled processes”

© Rolf Pfeifer

The principle of “parallel, loosely coupled processes”

Intelligent behavior:• emergent from agent-environment interaction• based on large number of parallel, loosely

coupled processes• asynchronous• coupled through agent’s sensory-motor system

and environment

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Artificial Fish “Wanda”

© Rolf Pfeifer

Artificial Fish “Wanda”: Exploiting morphology and system-environment interaction

1 DOF actuation (DOF=Degree Of Freedom)

controlling:- up-down- left-right- speed- reaching any point

in x, y, z-space

Design and construction:Horishi Yokoi

Fumiya IidaMark Ziegler

© Rolf Pfeifer

Design and construction:Horishi YokoiFumiya IidaMark Ziegler

Artificial Fish “Wanda”: Exploiting morphology and system-environment interaction

“cheap design”

© Rolf PfeiferDesign and construction:

Mark Ziegler

Artificial Fish “Findus”: Exploiting morphology and materials

“cheap design”

© Rolf Pfeifer

Case study: social behavior as a collection of reflexes

© Rolf Pfeifer

Kismet - the social interaction robot

Cynthia Breazeal, MIT Media Lab(previously MIT AI Lab)

Kismet

43D.MOV

© Rolf Pfeifer

Kismet - the social interaction robot

Cynthia Breazeal, MIT Media Lab(previously MIT AI Lab)

Kismet

Reflexes:- turn towards loud noise- turn towards moving objects- follow slowly moving objects- habituation

© Rolf Pfeifer

Kismet - the social interaction robot

Cynthia Breazeal, MIT Media Lab(previously MIT AI Lab)

Kismet

Reflexes:- turn towards loud noise- turn towards moving objects- follow slowly moving objects- habituation

“principle of parallel, looselycoupled processes”

© Rolf Pfeifer

Kismet - the social interaction robot

Cynthia Breazeal, MIT Media Lab(previously MIT AI Lab)

Kismet

Reflexes:- turn towards loud noise- turn towards moving objects- follow slowly moving objects- habituation

“principle of parallel, looselycoupled processes”

social competence as a collection of reflexes ?!??

© Rolf Pfeifer

Principle of “ecological balance”

balance in complexity• given task environment• match in complexity of sensory, motor, and

neural system

balance / task distribution between• morphology• neuronal processing (nervous system)• materials• environment

© Rolf Pfeifer

Principle of “ecological balance”

balance in complexity• given task environment• match in complexity of sensory, motor, and

neural system

balance / task distribution between• morphology• neuronal processing (nervous system)• materials• environment

© Rolf Pfeifer

Snail with giant eyes (Richard Dawkins)

ecologically unbalanced system

© Rolf Pfeifer

Braitenberg Vehicle 1 with large brain

ecologically unbalanced system

sensor for one quality(e.g. temperature, light)

one motor

very large brain

© Rolf Pfeifer

Principle of “ecological balance”

balance in complexity• given task environment• match in complexity of sensory, motor, and

neural system

balance / task distribution between• morphology• neuronal processing (nervous system)• materials• environment

© Rolf Pfeifer

Examples

• arm turning• loosely swinging arm• “Passive dynamic walker”• “Puppy”• “Stumpy”• cockroaches climbing over obstacles

© Rolf Pfeifer

Managing complex bodiesBrain-body cooperation

© Rolf Pfeifer

“Morphological computation” in cockroaches

(pictures and moviescourtesy Roy Ritzmann,Case Western Reserve Univ.)

© Rolf Pfeifer

“Morphological computation” in cockroaches

(pictures and moviescourtesy Roy Ritzmann,Case Western Reserve Univ.)

© Rolf Pfeifer

Self-regulating properties of coackroach body

brain: 1 Mio. neurons(rough estimate)

descending cells: 200 (!)

brain: - cooperation with local circuits- morphological changes (shoulder joint)

Watson, Ritzmann, Zill & Pollack, 2002, J Comp Physiol A

© Rolf Pfeifer

Changing “morphology”

Watson, Ritzmann, Zill & Pollack, 2002, J Comp Physiol A

shoulder jointconfiguration

brain:1 mio neurons

(unknown)

200 descendingneurons (!)

© Rolf Pfeifer

The redundancy principle

• redundancy prerequisite for adaptive behavior• partial overlap of functionality in different

subsystems• sensory systems: different physical processes

with “information overlap”

© Rolf Pfeifer

The redundancy principle

• redundancy prerequisite for adaptive behavior• partial overlap of functionality in different

subsystems• sensory systems: different physical processes

with “information overlap”

complementary to “cheap design”

© Rolf Pfeifer

Examples of redundancy principle

• different navigation systems of ants• hands for grasping/locomotion• legs/feet for manipulation• breaking systems in airplanes

© Rolf Pfeifer

The redundancy principle

• redundancy prerequisite for adaptive behavior• partial overlap of functionality in different

subsystems• sensory systems: different physical processes

with “information overlap”

complementary to “cheap design”

© Rolf Pfeifer

Vision-touch

• 100 eyes

© Rolf Pfeifer

Contents Lecture 2

• real worlds and virtual worlds• properties of complete agents• the quadruped „Puppy“ as a complex dynamical

system• illustration of selected design principles• summary

© Rolf Pfeifer

Summary Lecture 2

• intrinsic uncertainty in real world• properties of complete agents/dynamical systems• „cheap design“, self-stabilization / redundancy• parallel, loosely coupled processes• ecological balance

© Rolf Pfeifer

Agent design principles

Name Description

Three constituents Ecological niche (environment), tasks and agent must always be taken into account

Complete agents Complete agent must be taken into account, not only isolated components

Parallel, loosely coupled processes

Parallel, asynchronous, partly autonomous processes, largely coupled through interaction with environment

Sensory-motor coordination

Behavior sensory-motor coordinated with respect to target, self-generated sensory stimulation

Cheap design Exploitation of niche and interaction; parsimony

Redundancy Partial overlap of functionality based on different physical processes

Ecological balance Balance in complexity of sensory, motor, and neural systems; task dsitribution between morphology, materials, control, and interaction with environment

Value Driving forces: developmental mechanisms; self-organization

© Rolf Pfeifer

Thank you for your attention

stay tuned for lecture 3!