Spatial temporal patterns for action oriented perception in roving robots:
Gespeichert in:
| Weitere beteiligte Personen: | |
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| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin ; Heidelberg
Springer
2009
|
| Schriftenreihe: | Cognitive systems monographs
1 |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020446032&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | Literaturangaben |
| Umfang: | XX, 424 S. Ill., graph. Darst. 25 cm |
| ISBN: | 9783540884637 |
Internformat
MARC
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| 245 | 1 | 0 | |a Spatial temporal patterns for action oriented perception in roving robots |c Paolo Arena and Luca Patanè (eds.) |
| 264 | 1 | |a Berlin ; Heidelberg |b Springer |c 2009 | |
| 300 | |a XX, 424 S. |b Ill., graph. Darst. |c 25 cm | ||
| 336 | |b txt |2 rdacontent | ||
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| adam_text | Contents
Part I: Systems
1
Perception for Action in Insects
............................ 3
B. Webb, J. Wessnitzer
1.1
Introduction
............................................. 3
1.2
The Traditional View
..................................... 3
1.3
Perception as Transformation
.............................. 6
1.4
Closing the Loop
......................................... 8
1.4.1
Active Perception
.................................. 8
1.4.2
Dynamical Systems Theory and Perception
............ 10
1.4.3
Dynamics and Networks
............................. 11
1.4.4
Further Bio-inspired Architectures for
Perception-Action
.................................. 14
1.5
Predictive Loops
......................................... 16
1.6
Perception for Action in Insects
............................ 17
1.7
Basic Physiology and the Central Nervous System
............ 19
1.8
Higher Brain Centres in Insects
............................ 21
1.8.1
The Mushroom Bodies (Corpora Pedunculata)
......... 21
1.8.2
The Central Complex
............................... 27
1.9
Towards Insect Brain Control Architectures
................. 30
1.10
Conclusion
.............................................. 33
References
................................................... 35
2
Principles of Insect Locomotion
............................. 43
H. Cruse, V.
Dürr,
M.
Schilling,
J.
Schmitz
2.1
Introduction
............................................. 43
2.2
Biological Systems
........................................ 44
XVI Contents
2.3 Sensors.................................................. 48
2.3.1 Mechanosensors.................................... 49
2.3.2
Environmental
Sensors.............................. 51
2.4 Leg Controller........................................... 52
2.4.1 Swing
Movement
................................... 52
2.4.2
Stance Movement
.................................. 57
2.5
Coordination of Different Legs
............................. 65
2.6
Insect Antennae as Models for Active Tactile Sensors in
Legged Locomotion
....................................... 75
2.7
Central Oscillators
........................................ 78
2.8
Actuators
............................................... 83
2.9
Conclusion
.............................................. 85
References
................................................... 86
3
Low Level Approaches to Cognitive Control
................ 97
B. Webb, J. Wessnitzer, H.
Rosario,
M.
Szenher,
M. Zampoglou,
T.
Haferlach,
P.
Russo
3.1
Introduction
............................................. 97
3.2
Sensory
Systems and Simple
Behaviours
..................... 98
3.2.1
Mechanosensory Systems
............................ 98
3.2.2
Olfactory
Systems
.................................. 100
3.2.3
Visual Systems
..................................... 102
3.2.4
Audition
.......................................... 115
3.2.5
Audition and Vision
................................ 123
3.3
Navigation
.............................................. 129
3.3.1
Path Integration...................................
129
3.3.2
Visual
Homing.....................................
137
3.3.3
Robot
Implementation and Results
................... 143
3.4
Learning
................................................ 156
3.4.1
Neural Model and STDP
............................ 157
3.4.2
Non-elemental Associations
.......................... 158
3.4.3
Associating Auditory and Visual Cues
................ 163
3.5
Conclusion
.............................................. 166
References
................................................... 167
Part II: Cognitive Models
4
A Bottom-Up Approach for Cognitive Control
.............. 179
H. Cruse, V.
Dürr,
M.
Schilling,
J.
Schmitz
4.1
Introduction
............................................. 180
4.2
Behavior-Based Approaches
................................ 181
4.3
A Bottom-Up Approach for Cognitive Control
............... 185
4.4
Representation by Situation Models
........................ 188
4.4.1
Basic Principles of Brain Function
.................... 190
Contents XVII
4.4.2
Recurrent Neural Networks
.......................... 192
4.4.3
Memory Systems
................................... 192
4.4.4
Recurrent Neural Networks
.......................... 195
4.4.5
Applications
....................................... 199
4.4.6
Learning
.......................................... 203
4.5
Towards Cognition, an Extension of Walknet
................. 207
4.5.1
The Reactive and Adaptive Layer
.................... 208
4.5.2
Cognitive Level
.................................... 209
4.6
Conclusions
.............................................. 215
References
................................................... 216
Mathematical Approach to Sensory Motor Control and
Memory
.................................................... 219
M.G. Velarde, V.A. Makarov, N.P. Castellanos, Y.L. Song,
D.
Lombardo
5.1
Theory of Recurrent Neural Networks Used to Form Situation
Models
.................................................. 219
5.1.1
RNNs as a Part of a General Memory Structure
........ 219
5.1.2
Input Compensation
(1С)
Units and RNNs
............ 220
5.1.3
Learning Static Situation«
........................... 223
5.1.4
Dynamic Situations: Convergence of the Network
Training Procedure
................................. 229
5.1.5
Dynamic Situations: Response of Trained
1С-
Unit
Networks to a Novel External Stimulus
................ 236
5.1.6
IC-Networks with Nonlinear Recurrent Coupling
....... 242
5.1.7
Discussion
......................................... 246
5.2
Probabilistic Target Searching
............................. 249
5.2.1
Introduction
....................................... 249
5.2.2
The Robot Probabilistic Sensory
-
Motor Layers
........ 250
5.2.3
Obstacles, Path Complexity and the Robot IQ Test
..... 253
5.2.4
First Neuron: Memory Skill
.......................... 254
5.2.5
Second Neuron: Action Planning
..................... 257
5.2.6
Conclusions
........................................ 259
5.3
Memotaxis Versus Chemotaxis
............................. 260
5.3.1
Introduction
....................................... 260
5.3.2
Robot Model
...................................... 261
5.3.3
Conclusions
........................................ 265
References
................................................... 266
řVom
Low to High Level Approach to Cognitive Control
.... 269
P. Arena, S.
De Fiore,
M.
Frasca, D. Lombardo,
L.
Palane
6.1
Introduction
............................................. 269
6.2
Weak Chaos Control for the Generation of Reflexive
Behaviours
.............................................. 270
XVIII
Contents
6.2.1
The Chaotic Multiscroll System
...................... 272
6.2.2
Control of the Multiscroll System
..................... 272
6.2.3
Multiscroll Control for Robot Navigation Control
....... 275
6.2.4
Robot Navigation
.................................. 276
6.2.5
Simulation Results
................................. 278
6.3
Learning Anticipation in Spiking Networks
.................. 279
6.3.1
The Spiking Network Model
......................... 281
6.3.2
Robot Simulation and Controller Structure
............ 284
6.3.3
Spiking Network for Obstacle Avoidance
.............. 286
6.3.4
Spiking Network for Target Approaching
.............. 289
6.3.5
Navigation with Visual Cues
......................... 293
6.4
Application to Landmark Navigation
........................ 295
6.4.1
The Spiking Network for Landmark Identification
...... 297
6.4.2
The Recurrent Neural Network for Landmark
Navigation
........................................ 298
6.4.3
Simulation Results
................................. 301
6.5
Conclusions
.............................................. 305
References
................................................... 306
7
Complex Systems and Perception
........................... 309
P. Arena, D.
Lombardo, L. Palane
7.1
Introduction
............................................. 309
7.2
Reaction-Diffusion Cellular Nonlinear Networks and
Perceptual States
......................................... 311
7.3
The Representation Layer
................................. 312
7.3.1
The Preprocessing Block
............................ 313
7.3.2
The Perception Block
............................... 313
7.3.3
The Action Selection Network and the DRF Block
...... 320
7.3.4
Unsupervised Learning in the Preprocessing Block
...... 321
7.3.5
The Memory Block
................................. 323
7.4
Strategy Implementation and Results
....................... 325
7.5
SPARK Cognitive Architecture
............................. 330
7.6
Behaviour Modulation
.................................... 333
7.6.1
Basic Behaviors
.................................... 333
7.6.2
Representation Layer
............................... 334
7.7
Behaviour Modulation: Simulation Results
................... 334
7.7.1
Simulation Setup
................................... 334
7.7.2
Learning Phase
.................................... 336
7.7.3
Testing Phase
...................................... 336
7.8
Conclusions
..............................................
337
References
...................................................
338
Appendix I
-
CNNs and Turing patterns
......................... 340
Appendix II
-
From Motor Maps to the Action Selection Network
... 344
Contents XIX
Part III: Software/Hardware Cognitive Architecture and
Experiments
8
New Visual Sensors and Processors
......................... 351
L. Alba, R.
Domínguez
Castro, F.
Jiménez-
G
arrido,
S.
Espejo,
S.
Morillas,
J.
Listan,
C.
Utrera, A. García, Ma.D. Pardo,
R.
Romay,
С.
Mendoza, A. Jiménez, A. Rodríguez-Vázquez
8.1
Introduction
............................................. 351
8.2
The Eye-RIS Vision System Concept
........................ 353
8.3
The Retina-Like Front-End: From
ACE Chips
to Q-Eye
....... 356
8.4
The Q-Eye Chip
.......................................... 358
8.5
Eye-RIS
vi. 1
Description
(АСЕ 16К
Based)
.................. 362
8.5.1
Interrupts.........................................
364
8.6
Eye-RIS
vi.
2
Description (Q-Eye
Based)
.................... 364
8.6.1
Digital
Input/Output
Ports
.......................... 366
8.7
NIOS
II
Processor........................................
367
8.7.1
NIOS
II
Processor
Basics
............................ 368
8.8
Conclusion
.............................................. 368
References
................................................... 368
9
Visual Algorithms for Cognition
............................ 371
Á.
Zarándy, Cs. Rekeczky
9.1
Global Displacement Calculation
........................... 371
9.2
Foreground-Background Separation Based Segmentation
....... 374
9.2.1
Temporal Foreground-Background Separation
.......... 375
9.2.2
Spatial-Temporal Foreground-Background Separation
... 376
9.3
Active Contour Algorithm
................................. 377
9.4
Multi-target Tracking
..................................... 380
9.5
Conclusions
.............................................. 383
References
................................................... 383
10
SPARK Hardware
.......................................... 385
L. Alba, P. Arena, S.
De Fiore,
L. Patané
10.1
Introduction
............................................. 385
10.2
Multi-sensory Architecture
................................. 386
10.2.1
Spaxk Main Board
.................................. 387
10.2.2
Analog Sensory Board
.............................. 388
10.3
Sensory System
.......................................... 391
10.4
Conclusion
.............................................. 396
References
................................................... 397
11
Robotic Platforms and Experiments
........................ 399
P. Arena, S.
De Fiore, D. Lombardo, L. Patané
11.1
Introduction
............................................. 399
11.2
Robotic Test Beds: Roving Robots
.......................... 400
XX
Contents
11.2.1 Rover
I
........................................... 400
11.2.2 Rover
II
........................................... 402
11.3
Robotic Test Beds: Legged
Robots.......................... 402
11.3.1 MiniHex .......................................... 402
11.3.2 Gregor
III
......................................... 404
11.4 Experiments
and Results
.................................. 405
11.4.1 Visual
Homing and
Hearing Targeting ................ 405
11.4.2
Reflex-Based Locomotion Control with Sensory
Fusion
............................................ 408
11.4.3
Visual Perception and Target Following
............... 409
11.4.4
Reflex-Based Navigation Based on WCC
.............. 411
11.4.5
Learning Anticipation via Spiking Networks
........... 413
11.4.6
Landmark Navigation
............................... 415
11.4.7
Turing Pattern Approach to Perception
............... 416
11.4.8
Representation Layer for Behaviour Modulation
........ 420
11.5
Conclusion
.............................................. 422
References
................................................... 422
Index
........................................................... 423
Author Index
................................................... 425
|
| any_adam_object | 1 |
| author2 | Arena, Paolo 1966- |
| author2_role | edt |
| author2_variant | p a pa |
| author_GND | (DE-588)118166549 |
| author_facet | Arena, Paolo 1966- |
| building | Verbundindex |
| bvnumber | BV036524081 |
| classification_rvk | ST 308 |
| classification_tum | DAT 815f PSY 205f |
| ctrlnum | (OCoLC)319860404 (DE-599)BVBBV036524081 |
| dewey-full | 629.89263 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.89263 |
| dewey-search | 629.89263 |
| dewey-sort | 3629.89263 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Informatik Psychologie Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
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| id | DE-604.BV036524081 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T14:36:19Z |
| institution | BVB |
| isbn | 9783540884637 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-020446032 |
| oclc_num | 319860404 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM DE-355 DE-BY-UBR |
| owner_facet | DE-91 DE-BY-TUM DE-355 DE-BY-UBR |
| physical | XX, 424 S. Ill., graph. Darst. 25 cm |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Springer |
| record_format | marc |
| series | Cognitive systems monographs |
| series2 | Cognitive systems monographs |
| spellingShingle | Spatial temporal patterns for action oriented perception in roving robots Cognitive systems monographs Kognitives Schema (DE-588)4164480-3 gnd Biokybernetik (DE-588)4006846-8 gnd Autonomer Roboter (DE-588)4304075-5 gnd Automatische Handlungsplanung (DE-588)4211191-2 gnd Visuelle Wahrnehmung (DE-588)4078921-4 gnd Zeitwahrnehmung (DE-588)4067473-3 gnd |
| subject_GND | (DE-588)4164480-3 (DE-588)4006846-8 (DE-588)4304075-5 (DE-588)4211191-2 (DE-588)4078921-4 (DE-588)4067473-3 |
| title | Spatial temporal patterns for action oriented perception in roving robots |
| title_auth | Spatial temporal patterns for action oriented perception in roving robots |
| title_exact_search | Spatial temporal patterns for action oriented perception in roving robots |
| title_full | Spatial temporal patterns for action oriented perception in roving robots Paolo Arena and Luca Patanè (eds.) |
| title_fullStr | Spatial temporal patterns for action oriented perception in roving robots Paolo Arena and Luca Patanè (eds.) |
| title_full_unstemmed | Spatial temporal patterns for action oriented perception in roving robots Paolo Arena and Luca Patanè (eds.) |
| title_short | Spatial temporal patterns for action oriented perception in roving robots |
| title_sort | spatial temporal patterns for action oriented perception in roving robots |
| topic | Kognitives Schema (DE-588)4164480-3 gnd Biokybernetik (DE-588)4006846-8 gnd Autonomer Roboter (DE-588)4304075-5 gnd Automatische Handlungsplanung (DE-588)4211191-2 gnd Visuelle Wahrnehmung (DE-588)4078921-4 gnd Zeitwahrnehmung (DE-588)4067473-3 gnd |
| topic_facet | Kognitives Schema Biokybernetik Autonomer Roboter Automatische Handlungsplanung Visuelle Wahrnehmung Zeitwahrnehmung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=020446032&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035296331 |
| work_keys_str_mv | AT arenapaolo spatialtemporalpatternsforactionorientedperceptioninrovingrobots |
Inhaltsverzeichnis
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Teilbibliothek Stammgelände
| Signatur: |
0002 DAT 815f 2010 A 5260
Lageplan |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |