Field and Service Robotics: Results of the 5th International Conference

Peter Corke (Editor), Salah Sukkarieh (Editor)9783540334521, 3540334521

The 5th International Conference on Field and Service Robotics (FSR05) was held in Port Douglas, Australia, on 29th – 31st July 2005, and brought together the worlds’ leading experts in field and service automation. The goal of the conference was to report and encourage the latest research and practical results towards the use of field and service robotics in the community with particular focus on proven technology. The conference provided a forum for researchers, professionals and robot manufacturers to exchange up-to-date technical knowledge and experience.Field robots are robots which operate in outdoor, complex, and dynamic environments. Service robots are those that work closely with humans, with particular applications involving indoor and structured environments. There are a wide range of topics presented in this issue on field and service robots including: Agricultural and Forestry Robotics, Mining and Exploration Robots, Robots for Construction, Security & Defence Robots, Cleaning Robots, Autonomous Underwater Vehicles and Autonomous Flying Robots.This meeting was the fifth in the series and brings FSR back to Australia where it was first held. FSR has been held every 2 years, starting with Canberra 1997, followed by Pittsburgh 1999, Helsinki 2001 and Lake Yamanaka 2003.

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Table of contents :
front-matter.pdf……Page 1
2 Background……Page 16
3 Operating Principle……Page 17
4 System Description……Page 19
5 Results……Page 20
1 Definition……Page 22
2 Brief History……Page 25
References……Page 27
1 Introduction……Page 29
3 Tracking Approach……Page 31
4.1 Structure from Motion……Page 32
4.2 Camera Frame to World Frame……Page 34
4.3 Bundle Adjustment……Page 35
5.2 Tracking……Page 36
6 Conclusions……Page 38
References……Page 40
1 Introduction……Page 41
2.1 Vehicle……Page 42
3 Optimised Vision-Based Motion Estimation……Page 43
3.1 Three-Way Feature Matching……Page 44
3.2 Motion Estimation……Page 46
4 Experimental Results……Page 49
5 Conclusion……Page 51
References……Page 52
1 Introduction……Page 53
2 Algorithm 1: Robust Model Fitting……Page 55
3 Algorithm 2: Basic Morphological Operations……Page 56
4 Contrast Filtering……Page 57
5 Experimental Results……Page 58
5.1 Comparison Results……Page 60
6 Future Work……Page 61
7 Conclusion……Page 62
References……Page 64
1 Introduction……Page 65
2 Background……Page 67
3 The Structure of the Road Environment……Page 68
4.1 Review of Regular Polygon Detection……Page 69
4.2 Detecting Regular Polygons of Known Orientation……Page 70
4.3 Embodied Vision Issues……Page 71
6 Results……Page 72
References……Page 75
1 Introduction……Page 77
3 Distinctivness Analysis……Page 78
3.1 Mathematical Distinctness……Page 79
3.3 Probability of Similarity……Page 80
4.1 Initial Test of the Algorithm……Page 82
4.2 Global Distinctness Test……Page 83
4.3 Stability Test……Page 85
5 Conclusion and Future Work……Page 87
References……Page 88
1 Introduction……Page 89
3 Bimodal Active Vision……Page 90
3.1 Peripheral Perception……Page 91
3.2 Foveal Perception……Page 92
3.3 Bimodal Results……Page 98
4 Conclusion……Page 99
References……Page 100
1 Background……Page 101
2.1 Outline……Page 102
3.2 Design Decisions……Page 103
4.2 Map……Page 104
4.3 Marking Device……Page 105
4.4 Navigation……Page 106
5 Localization……Page 107
5.2 Pillars……Page 108
6 Experimental Evaluation and Modi.cations……Page 109
6.1 Modi.cations……Page 110
7 Summary and Conclusion……Page 111
References……Page 112
1 Introduction……Page 113
2 Approach……Page 114
3 Experimental Setup……Page 115
5 Estimation of Angular Pro.les……Page 116
5.1 A Di.erential Observation Technique for Angular Consistency Models……Page 117
5.3 A Two Dimensional Angular Consistency Model……Page 119
5.5 Information Theoretic Properties of Two Dimensional Angular Pro.les……Page 121
5.6 Other Applications and Extensions……Page 122
6 Conclusion and Future Work……Page 123
References……Page 124
1 Introduction……Page 125
2.1 Robotic Platform……Page 126
2.4 Node Detection……Page 127
2.5 Framework for Topological Uncertainty……Page 128
3.1 Comparison of Topological Properties……Page 129
3.2 2D Map Matching……Page 130
3.3 3D Map Matching……Page 131
3.4 Classi.cation……Page 132
4.2 Topological Matching……Page 133
4.4 3D Matching……Page 134
5 Conclusion……Page 135
References……Page 136
1 Introduction……Page 137
2.1 Older Solutions……Page 139
2.2 Current Products and Recent Solutions……Page 140
3.1 Metric Localization……Page 142
3.2 Topological Localization……Page 143
4 Navigation……Page 144
5.2 Trials from Test Mine……Page 146
6 Conclusions……Page 147
References……Page 148
1 Introduction……Page 149
2.1 RatSLAM……Page 150
3 Visual Learning……Page 151
3.1 Histogram Matching……Page 152
3.3 Orientation……Page 153
4.1 Robot Platform……Page 154
5 Results……Page 155
5.1 Local View Activity……Page 156
5.2 Pose Cell Trajectories……Page 157
6 Conclusion……Page 159
References……Page 160
1 Introduction……Page 161
2.1 New Measurements Used in D-SLAM……Page 163
2.2 Mapping in D-SLAM……Page 164
3.1 Data Association……Page 166
3.2 Recovery of the Feature Locations in D-SLAM……Page 167
4.1 Experimental Evaluation with a Pioneer Robot in an O.ce Environment……Page 168
5 Conclusions……Page 170
References……Page 172
1 Introduction……Page 173
2 Related Work……Page 174
3 Scan Matching Using Gaussian Sum Representation……Page 175
4 Scan Correlation Variance……Page 177
6 Scan-SLAM Update Step……Page 179
7 Results……Page 180
8 Conclusions and Future Work……Page 182
References……Page 184
1 Introduction……Page 185
2 Related Work……Page 186
3.2 Measurement Model……Page 187
4.1 Alignment Model……Page 189
4.2 Aligning Rigid Models……Page 190
5 Aligning Non-rigid Models……Page 192
5.1 Alignment Results……Page 195
6.1 Change Model……Page 196
6.2 Change Detection Results……Page 197
References……Page 199
1 Introduction……Page 201
2 Related Work……Page 203
3 Extended Elevation Maps……Page 204
4 E . cient Matching of Elevation Maps in 6 Dimensions……Page 206
5.1 Learning Accurate Elevation Maps from Multiple Scans……Page 208
5.2 Statistical Evaluation of the Accuracy……Page 209
References……Page 211
1 Introduction……Page 213
2 System Overview……Page 214
3 Vehicle Detection……Page 215
3.1 Construction of Vehicle Hypotheses……Page 216
3.2 Edge Filtering……Page 218
4 Map Construction……Page 219
4.1 Considering Previous Hypotheses……Page 220
5.1 Vehicle Detection……Page 221
6 Conclusion and Further Work……Page 222
References……Page 224
1 Introduction……Page 225
2.1 Example of the Haar Wavelet Transform in 1D……Page 227
2.2 The Haar Wavelet Transform in 2D……Page 228
3.1 Relation Between Sensor Measurement and Cell Occupancy……Page 230
3.2 Logarithmic-Form for Occupancy Grid Updates……Page 231
4 Multi-resolution……Page 232
5 Implementation……Page 233
6 Results……Page 234
7 Conclusion and Future Works……Page 235
References……Page 236
1 Introduction……Page 237
2 Related Work……Page 238
3 Approach……Page 239
4.1 Localization with Kalman Filter……Page 240
4.2 Localization with Particle Filter……Page 242
5.1 Formulation of Kalman Filter SLAM……Page 245
5.2 Results from Kalman Filter SLAM……Page 246
References……Page 248
1 Introduction……Page 249
3 Guiding Algorithm……Page 250
4.1 Search and Rescue Experiments……Page 251
4.2 Chemical Sensing Experiment……Page 255
4.3 Robot Navigation Experiment……Page 257
References……Page 260
1 Introduction……Page 261
2 Modelling Unstructured Environments……Page 263
3 Reasoning/Data Condensation……Page 264
4.2 Reasoning Tasks and Sensing Requirements……Page 266
4.3 The ‘International Rescue’ Project……Page 267
4.4 Experimental Results……Page 270
4.5 Future Work……Page 271
References……Page 272
1 Introduction……Page 273
2 Prior Work……Page 274
3.2 Constructing the State Lattice……Page 275
4.1 Path Decomposition……Page 277
4.2 Generating the Control Set……Page 278
5.1 Estimating the Search Heuristic……Page 280
5.2 Path Planner Results……Page 281
6 Applications……Page 282
References……Page 284
1 Introduction……Page 285
2.1 Modeling the Point of Contact……Page 287
2.2 Force-Closure Grasps……Page 289
3 Vision System Framework……Page 290
3.1 Extraction of Visual Features……Page 291
3.2 Edge Linking and Segment Fitting……Page 292
4 The Algorithm……Page 293
5 Results and Conclusions……Page 294
References……Page 296
1 Introduction……Page 297
2 Human Spatial Interaction……Page 298
3 The Control Strategy……Page 299
4 An Implementation……Page 300
4.1 Person Passage Method……Page 302
5.1 Person Passage……Page 303
5.2 Regular Obstacles Handling……Page 304
5.3 Pilot User Study……Page 306
6 Summary/Outlook……Page 307
References……Page 308
1 Introduction and Related Work……Page 309
2 Problem Overview……Page 311
3 Probabilistic Model De.nition……Page 312
4.1 Learning Discrete States and Observation Probabilities……Page 313
4.3 Learning Transition Probabilities……Page 315
5.1 Evaluation Criterion……Page 316
5.2 Results……Page 317
6 Conclusions……Page 318
References……Page 319
1 Introduction……Page 321
3 Kinematic Analysis……Page 323
4 Odometric Model and Slippage Detection……Page 325
5.1 Uphill and Horizontal Locomotion……Page 326
5.2 Downhill Locomotion……Page 328
6 Experimental Results……Page 329
7 Conclusions……Page 331
References……Page 332
1 Introduction……Page 333
2.1 Kinematics……Page 335
2.2 Adaptation to Our Prototype……Page 337
2.3 Derivation of Wheel Control Reference……Page 338
3.1 Computer Simulation……Page 340
3.3 Experiments……Page 341
4 Conclusion……Page 343
References……Page 344
1 Introduction……Page 345
2 History of Self-Propelled Movable Balls in View of U.S. Patents……Page 346
3 Fascinating Shape of a Sphere……Page 348
4.1 Submar……Page 349
4.2 Rollo……Page 350
4.3 The Next-Gen Robot Society……Page 352
4.4 Thistle……Page 354
6 Conclusions and Future of Ball-Shaped Robots……Page 355
References……Page 356
1 Introduction……Page 357
2 Overview of Design……Page 358
2.2 Construction……Page 359
3 Electrohydraulic Wobble Plate Motor……Page 360
3.1 Motor Sequencing Electronics and Operation……Page 361
3.2 Motor Torque Theory……Page 362
3.3 Cutting Head Performance……Page 363
3.4 Motor Experiments……Page 364
4.1 Steering Algorithm……Page 365
4.3 Embedded Software……Page 366
5 Adaptive Cutting Mechanisms……Page 367
References……Page 368
1 Introduction……Page 369
2 Selecting a Platform for Control of a Field Robot……Page 371
3 System Design……Page 372
4 Field Use of the System……Page 376
5 Summary……Page 377
References……Page 378
1 Introduction……Page 379
2 ISO 11783……Page 380
3 Methodologies and Tools……Page 381
4.1 Component Types……Page 382
4.2 Con.gurability……Page 383
5.1 Machine Modes……Page 384
5.3 User Interface Design……Page 385
6.2 Finite State Machines……Page 386
7 Simulation and Debugging……Page 387
8.1 Pneumatic Combined Seed and Fertilizer Drill……Page 388
9 Conclusions……Page 389
References……Page 390
1 Introduction……Page 391
2 Problem De.nition and Assumption……Page 392
3 Target Robot……Page 393
4.1 Path Planning……Page 395
4.3 Navigation Performance in Real Environment……Page 396
5 Putting a Plug into an Outlet……Page 397
5.2 Adjustment of Hand’s Position……Page 398
5.4 Judgement of Completion of the Insertion……Page 399
5.6 Discussion in Failure Cases of the Plug Insertion……Page 401
References……Page 402
1 Introduction……Page 403
2 Synthesis of the Bird’s-Eye View Images to Improve Remote Controllability……Page 405
3.1 Scan Matching……Page 407
3.3 Robot Positioning Experiment……Page 409
4 Implementation of the Synthesized Scene Recollection……Page 411
5 Conclusion……Page 412
References……Page 414
1 Introduction……Page 415
2 System Concept and Mission Scenario……Page 416
3 Mobile Robot Test Bed……Page 417
4.1 High Resolution 3D Geometry Acquisition of a Remote Environment……Page 420
4.2 Telepresence Technique Combining Model-Based and Image-Based Approaches……Page 421
5 Remote Navigation of the Robot……Page 423
6 Conclusions……Page 424
References……Page 425
1 Introduction……Page 426
2.1 Design Methodology……Page 427
2.2 ”OS4” Quadrotor Design……Page 428
3.1 Moments Acting on a Quadrotor……Page 433
3.2 Forces Acting on a Quadrotor……Page 434
4 Simulation……Page 435
6 Conclusion……Page 436
References……Page 437
1 Introduction……Page 438
2.1 Mechanical Structure……Page 439
2.2 Solar generator, Battery and Propulsion System……Page 440
3.2 Sensors……Page 441
3.3 Ground Control Station……Page 443
3.4 Autopilot Design Results……Page 444
4.1 Study of Various Scenarios……Page 445
7 Conclusion……Page 448
References……Page 449
1 Introduction……Page 450
2 Basic Vehicle Model……Page 451
2.1 Attitude Representations……Page 453
4 Vertical Flight Control and Guidance……Page 454
6 Transition Mode Guidance……Page 456
7 Flight State Logic……Page 457
7.1 Controller Transitions……Page 458
8 Implementation Details and Results……Page 459
9 Conclusion and Future Work……Page 460
References……Page 461
1 Introduction……Page 462
2.1 Platforms……Page 463
2.3 Environment……Page 464
3 Algorithmic Architecture……Page 465
4.1 Control Module……Page 466
4.2 Guidance Module……Page 467
4.4 The State Machine……Page 469
5.2 HardWare In the Loop Simulation (HWIL)……Page 470
6 Conclusion and Future Work……Page 471
References……Page 473
1 Introduction and Notation……Page 474
1.2 Prior Work……Page 475
2.1 Rate Kinematics, Actuator Dynamics, and Wheel Slip……Page 476
2.3 Kinetic Motion Model……Page 477
2.4 Trajectory Kinematics……Page 478
3.2 Control Primitives……Page 479
4 Application to the Rocky 7 Rover……Page 480
4.4 Rocky 7 Trajectory Kinematics……Page 481
5.3 Initialization/Termination……Page 482
6.1 Rough Terrain Trajectory Generation Example……Page 483
7 Conclusions……Page 484
References……Page 485
1 Introduction……Page 486
2 Related Work……Page 487
3.1 Obstacle Detection……Page 488
3.2 Collision Avoidance……Page 491
References……Page 498
1.1 Research Background……Page 500
1.2 Research Trends……Page 501
2.1 Sole Sensors for COF Estimation……Page 502
2.2 Error Tolerance and Appropreate Bias to Each FSR……Page 503
2.3 Mechanical Structure of Active Ankles……Page 504
3.1 Adaptation Algorithm……Page 505
3.2 Experiment, Adapt a Foot to a Slight Slope……Page 507
4.1 Detectable Footholds with Passive Ankles and Sole Sensors……Page 509
References……Page 511
1 Introduction……Page 512
2 Analytical Model……Page 514
3 Multi-solution Manner of Track-Terrain Interaction Model……Page 516
4 Implementation of Identification Technique……Page 518
5 Identification Results and Discussion……Page 519
6 Conclusion and Future Work……Page 521
References……Page 522
A.2 Compact sand, silt and loam, and frozen snow……Page 523
1 Introduction……Page 524
2 Research Platform……Page 525
3 3D-Odometry……Page 526
4 Wheel Slip Minimization……Page 528
5 Sensor Fusion……Page 532
6 Conclusion……Page 534
References……Page 535
1 Introduction……Page 536
1.2 A New Approach……Page 537
2 Experimental Procedure……Page 538
3.1 Vehicle Force Balance……Page 540
3.2 Braking Force……Page 542
4 Deriving the Model……Page 543
4.1 Formulating the Model……Page 544
4.2 Experimental Results……Page 545
5.2 Predicting Vehicle Tip-Over Condition……Page 546
References……Page 547
1 Introduction……Page 548
2.1 Machine……Page 549
2.2 Control Structure……Page 550
3 Laser-Based Self Calibration……Page 552
4.1 Terrain Mapping……Page 553
5.2 Stall Path Modi.cation……Page 554
5.3 Digging……Page 556
5.4 Detecting Dipper Fullness Using Motor Signals……Page 557
6 Conclusions……Page 558
References……Page 559
1 Introduction, Objectives and Approach……Page 560
2 Inspection Strategy and Systems……Page 561
2.1 Rough Inspection System (Spy)……Page 562
2.2 Inspection Systems……Page 563
3 Positioning, Pipe Axis Measurement……Page 564
4 Types of Damage and Selected Sensor Systems for Damage Detection……Page 565
4.1 Chemical Corrosion……Page 566
4.3 Crack Detection in Concrete Pipe……Page 567
4.4 Deviation of Pipe Position……Page 569
5 Summary and Outlook……Page 570
References……Page 571
1 Introduction……Page 572
2.1 Method……Page 573
2.2 Application for the Weeding Robot……Page 574
2.3 Results of the Design Process……Page 577
3 The Vehicle……Page 579
4 Navigation Along the Row……Page 581
5 Conclusions……Page 582
References……Page 583
1 Introduction……Page 584
2.1 Steering System of Wheel Loader……Page 585
2.2 Path Planning with Path Elements……Page 586
3.1 Resistance Force Applied on Bucket……Page 589
3.2 Pile Model……Page 590
3.3 Determination of Scooping Direction……Page 591
4 Experimental Result……Page 592
References……Page 595
1 Background and Introduction……Page 596
2 System Overview……Page 597
2.1 Communication……Page 598
2.2 Sensors and Actuators……Page 599
2.3 Development Strategy……Page 600
3 Infrastructure for Software Developmen……Page 601
4.1 Follow-the-Past Algorithm……Page 603
5 Status, Experiences and Future Work……Page 606
References……Page 607
back-matter.pdf……Page 608