The playful machine: theoretical foundation and practical realization of self-organizing robots
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin ; Heidelberg
Springer
2012
|
| Ausgabe: | Softcover re-print of the Hardcover, 1st edition |
| Schriftenreihe: | Cognitive systems monographs
volume 15 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Klappentext |
| Beschreibung: | XX, 333 Seiten Illustrationen, Diagramme |
| ISBN: | 9783662506332 |
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Datensatz im Suchindex
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| adam_text | Contents
1 introduction.......................................................... 1
2 Self-Organization in Nature and Machines.............................. 9
2.1 Self-Organization — The Physical Perspective ................ 10
2.1.1 Phase Transitions ..................................... 10
2.1.2 Convection Patterns...................................... 10
2.1.3 Reaction-Diffusion Systems .............................. 13
2.1.4 Examples from Biology ................................... 14
2.2 Self-Organization in Machines................................... 16
2.2.1 Swarms and Multi-Robot Systems .......................... 17
2.2.2 Behavioral Self-Organization............................. 18
2.3 Exploiting Self-Organization for Robot Control .............. 20
2.3.1 Mechanisms of Self-Organization ......................... 20
2.3.2 Self-Organization of Robot Behavior ..................... 20
3 The Sensorimotor Loop................................................ 23
3.1 Sensorimotor Loop — The General Case ........................ 24
3.1.1 The Controller .......................................... 24
3.1.2 Forward Model and Sensorimotor Dynamics ................. 25
3.2 Dominated by Embodiment: The Barrhl.......................... 27
3.2.1 Properties .............................................. 28
3.2.2 Open Loop Control ....................................... 28
3.2.3 Closed Loop Control ..................................... 30
3.3 Analyzing the Loop .......................................... 33
3.3.1 Feedback Strength ....................................... 35
3.3.2 Fixed Points ............................................ 36
3.3.3 Dynamics as Gradient Descent ............................ 37
3.3.4 The Effective Bifurcation Point ......................... 38
3.3.5 Effective Bifurcation Point and Explorative Behavior.. 41
3.4 Extending the Parameter Space ............................... 45
3.4.1 Bifurcation Scenario..................................... 45
XVI
Contents
3.4.2 Application: Biasing the Behavior .................... 47
3.5 Expanding the Body .................-........................ 48
3.6 Realization by Neural Networks .............................. 50
3.6.1 Rate-Coding Neuron Model ............................. 50
3.6.2 Supervised Learning .................................. 51
3.6.3 Feed-Forward Networks ................................. 52
3.6.4 Recurrent Networks.................................... 53
3.7 Summary........................................................ 54
Appendix 3.A Mathematical Details ................................ 55
3.A.1 Stability Analysis ................................... 55
3.A.2 Determining the Effective Bifurcation Point............ 56
4 Principles of Self-Regulation — Homeostasis........................ 59
4.1 History and Development of Homeostasis ...................... 60
4.1.1 Ashby’s Approach ...................................... 60
4.1.2 TheHomeostat ......................................... 61
4.1.3 Learning Homeostat... ................................ 63
4.1.4 Relating Time Scales ................................... 63
4.2 Self-Regulation ............................................ 64
4.2.1 First Ideas .......................................... 64
4.2.2 Learning the Controller from Specialized Models ...... 66
4.2.3 Homeostasis: Self-Regulated Stability................... 68
4.2.4 Conclusions and Outlook .............................. 71
Appendix 4.A Learning a Behavior from its Forward Model .......... 71
Appendix 4.B A Bootstrapping Scenario............................... 73
5 A General Approach to Self-Organization — Homeokinesis............. 75
5.1 Homeokinesis — Introduction................................... 76
5.1.1 Time-Loop Error..............,........................ 76
5.1.2 Discussion............................................. 80
5.1.3 Standard Setting .................................... 80
5.1.4 Landscape of the Time-Loop Error ....................... 81
5.2 Homeokinetic Learning ....................................... 83
5.2.1 Canonical Learning Rule ................................ 84
5.2.2 Explicit Learning Rules .............................. 85
5.2.3 Self-Actualization, Adaptivity, and Sensitivity — Example 86
5.2.4 The Homeokinetic Barrel ................................ 88
5.3 Key Features of Homeokinesis................................. 89
5.3.1 Homeokinesis as a Self-Referential Dynamical System ... 90
5.3.2 Sensitization — The Driving Force of Homeokinesis..... 91
5.3.3 State-Parameter Interplay ............................ 92
5.3.4 Temperature Effect ................................... 95
5.3.5 Symmetry Groups as Attractors* ........................ 96
5.3.6 Spontaneous Symmetry Breaking ......................... 99
Appendix 5.A Formalizations ..................................... 99
Contents
XVII
Appendix 5.B Effective States .................................... 100
Appendix 5.C Average Gradient..................................... 101
Appendix 5.D Remarks on Reconstruction vs. Postdiction ........... 103
Appendix5.E Derivation of Eq. (5.16) ........................... 103
Appendix 5.F Derivation of Eqs. (5.22, 5.23) ..................... 104
Appendix 5.G Moore-Penrose Pseudoinverse ......................... 105
6 From Fixed-Point Flows to Hysteresis Oscillators..................107
6.1 Time-Loop Error in One-Dimensional Systems ................... 108
6.2 Explicit Learning Rules and Fixed Point Flows ................ 108
6.2.1 Learning Rule.......................................... 109
6.2.2 Learning under Real World Conditions ................. 110
6.2.3 Relation to the Effective Bifurcation Point* ......... Ill
6.3 Extending the Parameter Space — The Hysteresis Oscillator.... 112
6.4 Embodiment and Situatedness — Robotic Experiments ........... 115
6.4.1 Wheeled Robots ........................................ 115
6.4.2 Spontaneous Cooperation in a Chain of Wheeled Robots 116
6.4.3 Emergent Locomotion of the Slider Armband ............. 119
6.5 Relation to Other Systems ................................... 120
Appendix 6.A Fixed-Point Flow...................................... 122
Appendix 6.B Towards the Effective Bifurcation Point ............. 123
Appendix 6.C Frequency of Hysteresis Oscillations ................ 124
7 Symmetries, Resonances, and Second Order Hysteresis...............127
7.1 Properties of the Two-Dimensional Sensorimotor Loop ......... 127
7.1.1 Two-Dimensional Loop .................................. 127
7.1.2 Bifurcation Scenario .................................. 128
7.1.3 Properties of SO (2) Dynamics ......................... 129
7.1.4 The Effect of the Bias ............................... 131
7.2 Homeokinetic Learning ........................................ 131
7.2.1 State-Parameter Dynamics .............................. 132
7.2.2 Oscillatory Behavior .................................. 134
7.2.3 Low Frequency Oscillations ............................ 136
7.2.4 Theory of Oscillatory Modes* .......................... 139
7.3 Second Order Hysteresis....................................... 140
7.3.1 Bias Dynamics and SO (2) Oscillations ................. 140
7.3.2 Frequency Sweeping and Hysteresis in Frequency Space 142
7.3.3 Frequency Sweeping in Real Systems..................... 143
7.3.4 Frequency Sweeping in 3D .............................. 145
7.4 Resonances — A Case for Embodiment........................... 146
Appendix 7. A Properties of Oscillatory Modes..................... 149
7.A.1 Derivation of Eq. (7.16)............................... 150
7.A.2 The Period-4 Cycle .................................... 150
xvm
Contents
8 Low Dimensional Robotic Systems.................................. 153
8.1 Semni....................................*................ 154
8.1.1 Construction .................................... 154
8.1.2 Experiments ........................................ 156
8.2 Spherical ............................................— 162
8.2.1 Construction ....................................... 162
8.2.2 Self-Exploration of Rolling Modes................... 163
8.2.3 Situatedness — How the Environment Shapes the Behavior 165
8.2.4 Situatedness—- Adapting to the Environment ......... 167
8.3 Slinging Snake............................................ 168
8.3.1 Construction ....................................... 169
8.3.2 Experiments ..................................... 170
8.4 Rocking Stamper .......................................... 172
8.4.1 Hardware ........................................... 173
8.4.2 Experiments ........................................ 175
8.5 Barrel .......................— —.......................... 178
8.5.1 Creativity in New Situations ...................... 178
8.5.2 Creativity Using the Real BARREL.................... 180
8.6 Summary.........................՛.......................... 182
9 Model Learning.................................................183
9.1 Cognitive Deprivation and Informative Actions ............. 185
9.1.1 Demonstration by the TwoWheeled... ................. 185
9.1.2 Deprivation Effect ................................. 187
9.1.3 Homeokinetic Learning and Bootstrapping .......... 188
9.1.4 Planar Snake........................................ 190
9.1.5 Spherical Robot in a Basin ...................... .— 192
9.1.6 Discussion.......................................... 193
9.2 Extending the Forward Model .............................. 193
9.2.1 Getting Misled by the Forward Model................. 194
9.2.2 Including the Sensor Branch ........................ 195
9.2.3 Ambiguity of the Extended Model .................... 195
9.2.4 Increasing Awareness of Causality .................. 196
9.2.5 Experiment with the SPHERICAL Robot ................. 197
9.3 Summary.................................................... 199
Appendix 9.A Ambiguities in the Sensorimotor Loop ............. 199
10 High-Dimensional Robotic Systems ................................. 201
10.1 Underactuated and Compliant .............................. 203
10.2 Dog and HippoDog......................................... 207
10.3 Humanoid ................................................. 209
10.4 Snakes — Adaptation and Spontaneity ...................... 216
10.5 Self-Rescue Scenario...................................... 218
10.6 World of Playful Machines .............................. 219
10.7 Discussion ............................................... 220
Contents
XiX
11 Facing the Unknown — Homeokinesis in a New Representation* .... 223
11.1 Interaction Representation of Sensorimotor Dynamics ........ 224
11.2 Extending the Time Horizon ................................. 226
11.2.1 Preliminaries: Orbits in Dynamical Systems........... 226
11.2.2 Interaction Representation of a Time Series ......... 228
11.2.3 Relation to the Time-Loop Error ..................... 229
11.2.4 General Multiple-Step Learning Rule ................. 230
11.3 Homeokinesis as a Flow of Lyapunov Exponents................ 230
Appendix 1 LA Proof of Eq. (11.13)............................... 232
Appendix 1 LB Derivation of the Interaction Representation ...... 233
12 Guided Self-Organization — A First Realization......................235
12.1 Integration of Problem Specific Error Functions ............ 236
12.2 Guidance by Teaching ....................................... 237
12.3 Direct Motor Teaching ...................................... 238
12.3.1 Experiment ........................................... 238
12.4 Direct Sensor Teaching and Distal Learning ................. 240
12.4.1 Experiment ........................................... 241
13 Channeling Self-Organization........................................243
13.1 From Spontaneous to Guided Symmetry Breaking ............... 244
13.2 Multiple Motor Relations ................................... 246
13.2.1 Guiding Towards Directed Locomotion .................. 246
13.2.2 Scaling Properties ................................... 250
13.3 Summary...................................................... 252
14 Reward-Driven Self-Organization.....................................253
14.1 Reinforcing Speed............................................ 254
14.2 Reinforcing Spin ............................................ 256
14.3 Discussion .................................................. 257
15 Algorithmic Implementation..........................................261
15.1 The sox Algorithm ........................................... 261
15.1.1 Extensions and Corresponding Meta-Parameters ......... 263
15.1.2 Putting it Together — The Universal Learning Rules .. 269
15.2 Cookbook for Playful Machines ............................... 271
15.2.1 Type of Robots — Mechanical Setup .................... 271
15.2.2 Initialization Procedures — Motor Babbling............ 272
15.2.3 Choosing the Meta-Parameters ......................... 273
15.2.4 Parameter Runaways — The Dark Side ................... 274
15.3 Increasing Internal Complexity .............................. 274
15.3.1 Controller Architecture............................... 275
15.3.2 Learning Rule......................................... 275
15.4 Generalized Pseudoinverse*................................... 277
15.4.1 Examples ............................................. 279
15.5 Simplified Algorithms ....................................... 280
XX
Contents
15.5.1 Avoiding Matrix Inversion ............................ 281
15.5.2 Matrix Inversion by Iteration......................... 281
15.6 Motor-Space Approach ........................................ 282
15.6.1 Reconstructing Previous Motor Values ................. 283
15.6.2 Learning Rules ...................................... 283
15.6.3 Using the Generalized Pseudoinverse .................. 284
Appendix 15.A Learning with Generalized Pseudoinverse ............ 285
Appendix 15.B Stability of the Gradient Descent .................. 286
15.B.1 Regularization of gf Terms ........................... 287
Appendix 15.C Learning Rules for Arbitrary Neuron Types .......... 287
Appendix 15.D Derivation of the Multilayer Learning Rule ......... 288
15.D.1 Algorithmic Realization ............................. 290
16 The LpzRobOTS Simulator............................................293
16.1 Structure ................................................... 294
16.2 Controller Framework ........................................ 294
16.3 Matrix Library ............................................. 295
16.4 Physics Simulator ........................................... 296
16.4.1 Rigid Body Dynamics — Open Dynamics Engine............ 297
16.4.2 Efficient Collision Detection ........................ 298
16.4.3 Material and Surface Properties........................ 298
16.4.4 Motors and Sensors.................................. 301
16.4.5 User Interaction .................................... 303
16.4.6 Creating the Virtual World ............................ 304
16.5 Highlights ................................................... 307
16.6 Summary....................................................... 308
16.6.1 Credits ........................................... 308
17 Discussion and Perspectives......................................... 309
List of Figures..........................................................313
List of Videos......................................................... 317
List of Experiments......................................................319
References.............................................................321
Index
331
The Cognitive Systems Monographs (COSMOS) publish new developments and
advances in the fields of cognitive systems research, rapidly and informally but
with a high quality. The intent is to bridge cognitive brain science and biology
with engineering disciplines. It covers all the technical contents, applications, and
multidisciplinary aspects of cognitive systems, such as Bionics, System Analysis,
System Modelling, System Design, Human Motion,Understanding, Human Activity
Understanding, Man-Machine Interaction, Smart and Cognitive Environments,
Human and Computer Vision, Neuroinformatics, Humanoids, Biologically
motivated systems and artefacts Autonomous Systems, Linguistic, Sports
Engineering, Computational Intelligence, Biosignal Processing, or Cognitive
Materials as well as the methodologies behind them. Within the scope of the
series are monographs, lecture notes, selected contributions from specialized
conferences and workshops, as well as selected PhD theses.
»COSMOS
Ralf Der · Georg Martius
The Playful Machine
Autonomous robots may become our closest companions in the near
future. While the technology for physically building such machines is
already available today, a problem lies in the generation of the behavior
for such complex machines. Nature proposes a solution: young children
and higher animals learn to master their complex brain ֊body systems
by playing. Can this be an option for robots? How can a machine be
playful? The book provides answers by developing a general principle
-homeokinesis, the dynamical symbiosis between brain, body, and
environment - that is shown to drive robots to selfdetermined, individual
development in a playful and obviously embodimentrelated way: a
dog-like robot starts playing with a barrier, eventually jumping or climbing
over it; a snakebot develops coiling and jumping modes; humanoids
develop climbing behaviors when fallen into a pit, or engage in
wrestling-like scenarios when encountering an opponent. The book also
develops guided selforganization, a new method that helps to make the
playful machines fit for fulfilling tasks in the real world.
The book provides two levels of presentation. Students and scientific
researchers interested in the field of robotics, self-organization and
dynamical systems theory may be satisfied by the in-depth mathematical
analysis of the principle, the bootstrapping scenarios, and the emerging
behaviors. But the book additionally comes with a robotics simulator
inviting also the non-scientific reader to simply enjoy the fabulous world
of playful machines by performing the numerous experiments.
|
| any_adam_object | 1 |
| author | Der, Ralf Martius, Georg |
| author_facet | Der, Ralf Martius, Georg |
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| author_sort | Der, Ralf |
| author_variant | r d rd g m gm |
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| classification_rvk | ST 308 |
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| dewey-full | 629.89263 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
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| dewey-sort | 3629.89263 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Informatik Elektrotechnik / Elektronik / Nachrichtentechnik Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| edition | Softcover re-print of the Hardcover, 1st edition |
| format | Book |
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| id | DE-604.BV044293118 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:48:57Z |
| institution | BVB |
| isbn | 9783662506332 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029697185 |
| oclc_num | 992552218 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR |
| owner_facet | DE-355 DE-BY-UBR |
| physical | XX, 333 Seiten Illustrationen, Diagramme |
| publishDate | 2012 |
| publishDateSearch | 2012 |
| publishDateSort | 2012 |
| publisher | Springer |
| record_format | marc |
| series | Cognitive systems monographs |
| series2 | Cognitive systems monographs |
| spelling | Der, Ralf Verfasser aut The playful machine theoretical foundation and practical realization of self-organizing robots Ralf Der and Georg Martius Softcover re-print of the Hardcover, 1st edition Berlin ; Heidelberg Springer 2012 2012 XX, 333 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Cognitive systems monographs volume 15 Computersimulation (DE-588)4148259-1 gnd rswk-swf Bahnplanung (DE-588)4267628-9 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Selbst organisierendes System (DE-588)4054424-2 gnd rswk-swf Automatische Handlungsplanung (DE-588)4211191-2 gnd rswk-swf Embodiment (DE-588)7627636-3 gnd rswk-swf Autonomer Roboter (DE-588)4304075-5 gnd rswk-swf Rückkopplung (DE-588)4050851-1 gnd rswk-swf Autonomer Roboter (DE-588)4304075-5 s Embodiment (DE-588)7627636-3 s Selbst organisierendes System (DE-588)4054424-2 s Automatische Handlungsplanung (DE-588)4211191-2 s Bahnplanung (DE-588)4267628-9 s Maschinelles Lernen (DE-588)4193754-5 s Computersimulation (DE-588)4148259-1 s Rückkopplung (DE-588)4050851-1 s DE-604 Martius, Georg Verfasser aut Erscheint auch als Online-Ausgabe 978-3-642-20253-7 Cognitive systems monographs volume 15 (DE-604)BV035296331 15 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029697185&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029697185&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Der, Ralf Martius, Georg The playful machine theoretical foundation and practical realization of self-organizing robots Cognitive systems monographs Computersimulation (DE-588)4148259-1 gnd Bahnplanung (DE-588)4267628-9 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Selbst organisierendes System (DE-588)4054424-2 gnd Automatische Handlungsplanung (DE-588)4211191-2 gnd Embodiment (DE-588)7627636-3 gnd Autonomer Roboter (DE-588)4304075-5 gnd Rückkopplung (DE-588)4050851-1 gnd |
| subject_GND | (DE-588)4148259-1 (DE-588)4267628-9 (DE-588)4193754-5 (DE-588)4054424-2 (DE-588)4211191-2 (DE-588)7627636-3 (DE-588)4304075-5 (DE-588)4050851-1 |
| title | The playful machine theoretical foundation and practical realization of self-organizing robots |
| title_auth | The playful machine theoretical foundation and practical realization of self-organizing robots |
| title_exact_search | The playful machine theoretical foundation and practical realization of self-organizing robots |
| title_full | The playful machine theoretical foundation and practical realization of self-organizing robots Ralf Der and Georg Martius |
| title_fullStr | The playful machine theoretical foundation and practical realization of self-organizing robots Ralf Der and Georg Martius |
| title_full_unstemmed | The playful machine theoretical foundation and practical realization of self-organizing robots Ralf Der and Georg Martius |
| title_short | The playful machine |
| title_sort | the playful machine theoretical foundation and practical realization of self organizing robots |
| title_sub | theoretical foundation and practical realization of self-organizing robots |
| topic | Computersimulation (DE-588)4148259-1 gnd Bahnplanung (DE-588)4267628-9 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Selbst organisierendes System (DE-588)4054424-2 gnd Automatische Handlungsplanung (DE-588)4211191-2 gnd Embodiment (DE-588)7627636-3 gnd Autonomer Roboter (DE-588)4304075-5 gnd Rückkopplung (DE-588)4050851-1 gnd |
| topic_facet | Computersimulation Bahnplanung Maschinelles Lernen Selbst organisierendes System Automatische Handlungsplanung Embodiment Autonomer Roboter Rückkopplung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029697185&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029697185&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035296331 |
| work_keys_str_mv | AT derralf theplayfulmachinetheoreticalfoundationandpracticalrealizationofselforganizingrobots AT martiusgeorg theplayfulmachinetheoreticalfoundationandpracticalrealizationofselforganizingrobots |