From AI to Robotics. Mobile, Social and Sentient Robots

406 Pages·2018·1.67 MB·English

by  Arkapravo Bhaumik

From A I to Robotics
Mobile, Social, and Sentient Robots
A R K A P R A V O B H A U M I K
CRC Press
Taylor & Francis Group
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Boca Raton, FL 33487-2742
© 2018 by Taylor & Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
Version Date: 20180205
International Standard Book Number-13: 978-1-4822-5147-0 (Hardback)
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Contents
Preface xiii
Section I Theory
hapter
C 1(cid:4) ...and then there were mobile robots 3
1.1 EARLYPIONEERSANDTHESTORYTILLSHAKEY 3
1.1.1 Walter‘s turtles 9
1.1.2 Shakey and the Stanford Cart 12
1.2 CURRENT-DAYMOBILEROBOTICS 14
1.3 CULTURALANDSOCIALIMPACT 19
1.3.1 Science fiction, entertainment industry, medical surgery and
military 20
1.3.2 Do robots pose a threat for human beings? 26
hapter
C 2(cid:4) Embodied AI, or the tale of taming the fungus eater 31
2.1 FROMAITOROBOTS 31
2.2 ARTIFICIALINTELLIGENCEFORROBOTS 31
2.2.1 What is an ‘agent’ ? 34
2.3 EMBODIEDAI-MAKINGOFAUTONOMOUSAGENTS 36
2.3.1 Toda’s model for fungus eaters 36
2.3.2 Design principles for autonomous AI agents 37
2.4 ANTHROPOMORPHISM — A TREASURE TROVE FROM MOTHER
NATURE 41
2.4.1 Concepts from semiotics — ‘UMWELT’ 41
2.4.2 Concepts from ecology — Uniqueness of vision 43
2.4.3 Concepts from psychology — Behaviourism 46
2.4.4 Artificial animals — ANIMAT 49
2.5 EVALUATINGPERFORMANCE-AIVS.ENGINEERING 65
2.6 THREEFORKSINTHEROAD 71
2.6.1 The problem of completeness — Planning is NP-hard 73
2.6.2 The problem of meaning — The symbol grounding problem 74
2.6.2.1 Solving the symbol grounding problem 75
2.6.3 The problem of relevance — The frame problem 77
2.6.3.1 Representations — The root of all evil 79
hapter
C 3(cid:4) Control paradigms for mobile robots 87
3.1 CONTROLPARADIGMS 87
3.2 BRAITENBERG’SVEHICLES1TO4—ENGINEERINGBEHAVIOUR 90
3.3 DELIBERATIVEAPPROACH 99
3.3.1 Shortcomings of the deliberative approach 99
3.3.2 From animals to robots 101
3.3.3 Robots and computers are fundamentally different 101
3.4 REACTIVEAPPROACH 103
3.4.1 Subsumption architecture and the nouvelle AI 105
3.4.2 Motor schema 108
3.4.3 Action selection & bidding mechanisms 111
3.5 ACRITIQUEOFTHENOUVELLEAI 114
3.5.1 Issues with the nouvelle AI 116
3.5.1.1 Implementation issues in subsumption architecture 116
3.5.1.2 Issues with motor schema 118
3.5.2 Extending reactive approach to higher functions 119
3.6 HYBRIDARCHITECTURES 122
Section II Implementation, or How to Make Robots
hapter
C 4(cid:4) Tools for a roboticist 131
4.1 THETOOLS:NAVIGATIONANDADAPTIVITY 131
4.2 NAVIGATION,PATHPLANNINGANDMAPPING 134
4.2.1 A∗ and bug algorithms 134
4.2.2 Considerations for navigation 135
4.2.3 Artificial potential fields 137
4.2.4 Nearness Diagram (ND) 146
4.2.5 Navigation in three dimensions 148
4.3 ADAPTIBILITYANDLEARNING 149
hapter
C 5(cid:4) Software, simulation & control 155
5.1 SOFTWAREFORROBOTICS 155
5.2 AVERYSHORTINTRODUCTIONTOROS 160
Section III Robot-Robot & Human-Robot Interactions
hapter
C 6(cid:4) Robot-robot interaction, groups and swarms 177
6.1 MANYROBOTSYSTEMS 177
6.2 NETWORKEDROBOTICS 178
6.3 SWARMROBOTICS 181
6.3.1 Relating agent behaviour to the collective behaviour 185
6.3.2 Signatures of swarm robotics 186
6.3.2.1 Minimalism: Non-intelligent robot, intelligent swarm 187
6.3.2.2 Stigmergy: Indirect interactions 187
6.3.2.3 Emergence: Swarm behaviour is difficult to model 188
6.3.2.4 Phase change: Disorder to order 189
6.3.2.5 Self organisation: A dynamically stable swarm 189
6.3.3 Metrics for swarm robotics 189
6.3.4 Swarm Engineering — Visions for a new technology 191
hapter
C 7(cid:4) Human-robot interaction and robots for human society 201
7.1 HUMAN-ROBOTINTERACTION 201
7.1.1 Distributed cognition 204
7.2 SOCIALROBOTICS 204
7.2.1 Design for social robots 207
7.2.1.1 Aesthetics 208
7.2.1.2 Facial traits 210
7.2.1.3 Natural language processing (NLP) 212
7.3 APPLICATIONS 214
7.3.1 Service robots, with a social face 214
7.3.1.1 CERO — Cooperative embodied robot operator 214
7.3.2 Robots in elderly care 217
7.3.2.1 Care-O-bot 3 — The smart butler 217
7.3.2.2 Hobbit — Returning a robot’s favour 217
7.3.3 Companion robot and robot therapy 218
7.3.3.1 Paro - The cute robotic seal 220
7.3.3.2 KASPAR — Kinesics and synchronization in
personal assistant robotics 222
7.3.4 Museum guide and receptionist robots 225
7.3.5 Functional robots, more than just smart machines 230
7.3.5.1 Explorer robots — new age fungus eaters 230
7.3.5.2 Search and rescue robots 231
7.4 JAPAN,ROBOTHISTORYINTHEMAKING 233
hapter
C 8(cid:4) Robots with moral agency, in the footsteps of Asimov 239
8.1 THENEEDFORTHEGOODROBOT 239
8.2 MORALITYANDETHICS 242
8.3 ASIMOV’S3LAWSANDTHEIRLIMITATIONS 250
8.4 ETHICALTHEORYFORROBOTS 257
8.4.1 Deontology 257
8.4.2 Consequentialism 259
8.4.3 Deontology vs. Consequentialism — The trolley problem 261
8.4.4 Implementing ethics as an architecture 265
8.4.4.1 The ethical architecture — action logic, in military
robots 265
8.4.4.2 Consequence engine — using fast simulations for
internal models 270
8.4.4.3 First implementation, development of a carer robot
with deontic ethics 272
8.4.5 Virtue ethics 272
8.5 SOCIALCHANGESANDTHENEARFUTURE 273
Section IV ... the Future
hapter
C 9(cid:4) Quest for the sentient robot 283
9.1 CANROBOTSBECONSCIOUS? 283
9.2 SELFAWARENESS,CONSCIOUSNESSANDFREEWILL 285
9.2.1 Self awareness 285
9.2.2 Consciousness 286
9.2.3 Free will 291
9.3 FROMMACHINESTO(NEAR)HUMANBEINGS 292
9.4 SEMI-SENTIENTPARADIGMANDIT‘SLIMITATIONS 297
9.5 MEMORIES,MEDITATIONANDTHEINNERWORLD 302
9.6 EXPERIMENTS — COG, MIRROR COGNITION AND THE 3 WISE
ROBOTS 304
9.6.1 From reactive architecture 304
9.6.1.1 Cog 305
9.6.1.2 Consciousness based architecture 306
9.6.2 From cross-modal bindings 309
9.6.2.1 Cog’s tambourine experiment 310
9.6.2.2 Nico’s drumming 310
9.6.3 Mirror cognition 312
9.6.3.1 A very simple implementation of the mirror test in
robots 312
9.6.3.2 Haikonen’s somatosensory model 313
9.6.3.3 Designing the mirror test with MoNADs 314
9.6.4 Psychometric AI — The knowledge game 321
hapter
C 10(cid:4) Super intelligent robots and other predictions 331
10.1 PEERINGINTOTHECRYSTALBALL 331
10.2 TWILIGHTORREBIRTHOFOURCIVILISATION? 336
10.3 SUPERINTELLIGENCE,FUTURETECHNOLOGYANDRAYKURZWEIL 342
10.3.1 Super intelligence 347
10.3.2 “To singularity and beyond” 350
10.3.3 Alternate opinions & containment of AI 356
ppendix
A A(cid:4) Running The Examples 361
A.1 BRAITENBERGSIMULATOR 361
A.2 WALLEEVACHAT 361
References 363
Index 389
Preface
Since Walter’s Turtles, technology has come a long way and we can now boast of
state-of-the-art robots, such as ASIMO, PR2, NaO and Pepper. My interest in this field
of study, which has taken on obsessive proportions, is due to my academic background,
my participation in various open source robotic communities (Player/Stage, ROS, MORSE
etc.), my teaching assignments and projects with my students and above all, a child-like
desire to make robots. Not withstanding my personal desire to put together nearly all that
I have learnt over the last ten years, robotics and AI truly stand to change the world as we
knowit.Inthistextspanningtenchapters,Ihavelookedtovariousresearchers;Braitenberg,
Dennett,Brooks,Arkin, Murphy, Winfield,Vaughan,Dudek,Dorigo, Sahin, Bekey,Abney,
Wendell,Takeno,BringsjordandtheAndersons,asthosewhohavehadalastingimpression
onmeandhaveshownmetheproverbiallighttothecorrectpath.Otherthantheseacademic
influencesandmotivation,sciencefiction,particularlyIsaacAsimov,PhilipK.Dick,Arthur
C. Clarke, Cory Doctorow, Peter Watts etc., led me to engaging queries on various aspects
of AI and robots and their influence on human society and helped me to illustrate ideas
in the later chapters. Furthermore, I have been influenced by and have enjoyed a long list
of movies, among which are iconic robot movies such as, Wall-E, IRobot and cult classics,
such as The Metropolis, Blade Runner and West World, and the more recent ones, such as
Interstellar, Real Steel, Robot and Frank, Big Hero 6 and Ex-Machina.
This text is meant for undergraduate students and may also serve as a reference for
graduate students. It attempts to introduce the reader to what has been achieved in
agent-based robotics over the last four decades, the ways we can implement such concepts
witheasilyavailableelectronicsandopensourcetools,multirobotteams,swarmroboticsand
human robot interaction, as well as the efforts to develop artificial consciousness in robots.
The last chapter is on the future of AI and robotics in the foreshadow of the prophecies of
super intelligent AI and technological singularity.
The journey starts with mythical lore from ancient Greece and ends with a debate on
a futuristic prophecy where human beings and technology merge to create superior beings
as heir to our evolutionary pathways. From Haphaestus to Philon to Da Vinci to Tesla to
Walter to Toda to Moravec to Braitenberg to Brooks to Kurzweil, this text is livened up
with examples, pictures, one-on-one chatter with experts, schematics and cartoons.
The seven broad themes addressed across the ten chapters are;
1. AI vs. Applied AI
There is always some contrast in the theory and the practice for any discipline, and the
appealforclassroomteachingversushands-onapplicationinthelaboratory,workshoporin
industryhashaditscontrasts.ItismanyfoldsmoreforAI.Ithasbeenmyexperiencethat
thequestionoftenboilsdowntoeither‘learnAI’or‘makerobots’.OutstandingtextsinAI
asRussellandNorvigandRichandKnightdon’treallyhelpmuchtowardsbuildingarobot,
and one has to dig out online tutorials, YouTube videos etc. The same is true for machine
FIGURE 1 The bridge from AI to applied AI. For new initiates the two domains appeal as
two different disciplines. An undergraduate student will find it difficult to see the convergence
of the doctrines of AI; for example, planning, search and knowledge representation are the
philosophical basis and analytical tools for making robots, but at a beginners level it reduces
to simple programming scripts, interfacing of sensors with motors and ease of design. Therefore,
the correlation between AI and robotics may not be very apparent to a young enthusiast.
learning; a text which introduces a student to neural network, such as Bishop is probably
the best treatment that one can offer on the subject, but to make a neural network, the
student will have to find suitable C or Python libraries. The bridge, as shown in Figure
1, between theory and application is not only distant but requires different faculties. It
is also to be added that AI, by itself is not enough to make robots; the effort calls for
electronics, mechanical design, sensor design and other overlapping disciplines, depending
onthespecificsoftherobot.Thebookmakesanefforttoshortenthisbridgeandhopefully,
make the crossing easier, by correlating concepts to their applications.
The applications cover designing simple behaviours in Chapter 2 and 3, navigation in
Chapter 4, and multirobot systems and swarming, many of these are supplemented with
examples from practical scenarios, algorithms and introduction to the software. Navigation
is unique as it is a basic behaviour and also a design tool. Chapter 5 has a few examples
with hardware which are meant as appetizers to whet the imagination and creativity of the
budding robot enthusiast.
2. Deliberative vs. Reactive and the Question of Relevance
Thisdebatebetweenthetwowaysofapproachingagent-basedroboticswastriggeredby
the pioneering work of Rodney Brooks in the mid 1980s. However, the thread of thought
can be traced back to behaviourism and phenomenology. Behaviourism was established as
a sub-discipline in psychology in late 1890s through the works of Pavlov, Thorndike and by
Skinner in 1950s. Philosophical development in phenomenology by Husserl, Heidegger and
Merleau-Pontyhelpedtocementtheconceptsofsituatednessandembodiment.Assimilation
of these ideas into robotics was done independently by three daring scientists, who had the
wish to create artificial creatures: Walter in late 1940s, Toda in mid 1960s and Braitenberg
in early 1980s. Walter explicitly demonstrated design of behaviour in his turtles, Toda
suggested the first models of autonomous agency and Braitenberg’s gedanken experiments
showed that simple agency can lead to very advanced performance. These independent
conclusions led to the basic principles of behaviour-based robotics.
The frame problem and the question of relevance is an inherent burden in designing a
robot and forms the crux of the argument. It cannot be eradicated, and has to be either
completely avoided as in behaviour-based paradigm, or consider addressing it to a minimal
asinPENGI.Insheercontrast,wehumanbeingscan‘solve’theframeproblem‘ontherun’.
Nowadays, most robots have deliberative as well as reactive modules and are supplemented
withmachinelearning,thusovercomingtheissueofrelevanceatleastinlow-levelrepetitive
behaviourscontainedinamoreorlessknownenvironment.However,thisuglymonsterraises
its head time and again. The utilitarianism vs. deontology debate for autonomous vehicles
is a direct extension of the deliberative vs. reactive quarrel, where all deontic approaches
are pegged to a set ‘frame’ of pre-programmed rules and utilitarian principles are based
on immediacy. Also, most attempts to develop conscious robots such as those discussed
in Chapter 9 are defacto inquiries into the question of relevance: Is the dynamics of a
tambourine relevant for its beat? Will looking into the mirror make the robot find its own
image?Canarobotappropriatecausality,andrelateactionstoconclusion?Iwouldwishto
believethatarobotwhichcan‘solve’theframeproblemacrossfivesensesashumanbeings
do, would be conscious, devoid of any shade of doubt.
Fodorclaimedthatduetotheframeproblem,AIisdead.Forwhatthelasttwodecades
of research has provided, the debate of the frame problem has added to the richness of AI.
3. Engineering Robot Behaviour
Mybestreferenceforunderstandingbehaviouris,RonaldArkin’stome,BehaviourBased
Robotics, and the works of Richard Vaughan and Alan Winfield, and a good part of the
book documents the engineering of desired behaviour in a robot.
Reactivesystemsarefasterandeasiertodesignthanthedeliberativeorhybridones,and
theydonotneedsleekhardwaresuchasacameraoralaserscanner.Theunwittingcontrast
is that since behaviour is emergent it is difficult to design the architecture for a desired
performance.Verysimplebehaviours,suchas‘trackalightsource’or‘followaline’,hardly
demonstrate the inherent relation between the agent and the environment. Swarm robotics
andBraitenbergvehicleshelptoillustratesuchintimaterelationsandcontrastoftheeaseof
designtotheunpredictablenatureofperformance.GerardoBeni,verycleverlysummarises
this phenomenon, that [robot] behaviour stands as a convergence of two radically different
ideas, unpredictability and the wish to find order. The definition of robot behaviour has
been modified over the last three decades, and may be further edited in the years to come.
Walter’sTurtleswasthebeginningofagentbasedrobotics,butitwaslefttoSimonand
later Toda, to envisage a self-sustaining mobile agency with local landmarks and multiple
goals which can negotiate tradeoff between its energy supply and the task at hand. The
fungus eaters mined uranium on a far off planet and gathered fungus which when digested
provided them with energy, Toda’s model was also a blueprint for early path planning
models. The Mars rovers can be said to be the modern-day avatars of the fungus eater,
though they harness their energy from solar panels and not Martian fungus.
In the 1980s, Wilson’s model of the ANIMATs, Pfeifer’s principles for design and
development of agent based robotics and Lumelsky and Stepanov’s Bug Algorithms were
motivated from mother nature and streamlined the principles for designing of automated
self-sustaining mobile agency.
Braitenberg’s vehicles are designs of more involved functionalities, as emotions, value
systems, correspondence of information, collating aspects of reality to memory, learning
andevolution,allofthesefromsimplesensory-motorprinciples.Braitenberg’svehicleshave
served as illustrative examples in a number of chapters and is a recurring theme across the
book.
AI has wilfully plagiarised from the natural world and anthropomorphic motivation in
design and behaviour models derived from ethological studies has been the trend. Best
examples are: Fukuda’s brachiatron was motivated from the swinging motion of apes;
ECOBOT series of robots modelled on the process of digestion; swarm behaviour designed