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List of Figures
xiv
T H E GRASPING H A N D
List of Figures Figure 1.1 Figure 1.2 Figure 1.3 Figure 2.1 Figure 2.2 Figure 2.3 Figure 2.4 Figure 2.5 Figure 2.6 Figure 2.7 Figure 2.8 Figure 2.9 Figure 2.10 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 Figure 3.5 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 4.5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Figure 4.10 Figure 4.1 1 Figure 4.12 Figure 4.13 Figure 4.14 Figure 4.15 Figure 4.16 Figure 4.17 Figure 4.18 Figure 5.1 Figure 5.2 Figure 5.3
Examples of prehension ............................... 5 The prehensile problem ................................ 7 Triangle strategy......................................... 9 Schlesinger classification .............................. 18 Napier classification.................................... 24 Cutkosky and Howe classification ...................26 Various postures ........................................ 28 Prehensile postures as oppositions ..................32 Grasping different sized mugs ........................ 33 Virtual fingers apply oppositions ..................... 34 Jacobson and Sperling coding system ...............38 Virtual finger geometric configuration ...............40 Black box mapping: object, task, postures ..........43 Wrist velocity and hand aperture .................... S O Velocity and aperture: two objects.................... 52 Arbib Coordinated Control Program .................54 Paillard model of reaching and grasping.............55 Greene ballpark model ................................. 56 LAMA robot task plan ................................ 66 Miller et al. TOTE (Test-Operate-Test-Exit) ........68 Three major brain systems ............................ 71 Levels of the CNS ..................................... 73 Paillard model of CNS ................................. 74 Objects viewed in 2D: pinch vs. clench..............78 Opposition vector ....................................... 82 Neural net for object, task, and oppositions ........85 Neural network for objects and oppositions ........88 Results of Uno et al . neural net ....................... 89 Neural network for virtual finger mapping ..........92 Expert system for opposition space ..................93 Kuperstein model for hand-eye coordination .......96 Iberall approach vector neural network ..............99 Iberall approach vector simulations ................100 Rosenbaum et a1. Orienting wrist for tasks........ 102 Stelmach et al. Orienting opposition space ........104 Approach vector ...................................... 106 Coordinated Control Program motor schemas.... 110 Homunculus in motor cortex........................ 113 Computational model of movement ................116
List of Figures Figure 5.4 Figure 5.5 Figure 5.6 Figure 5.7 Figure 5.8 Figure 5.9 Figure 5.10 Figure 5.11 Figure 5.12 Figure 5.13 Figure 5.14 Figure 5.15 Figure 5.16 Figure 5.17 Figure 5.18 Fiiure 5.19 Figure 5.20 Figure 5.21 Figure 5.22 Figure 5.23 Figure 5.24 Figure 5.25 Figure 5.26 Figure 5.27 Figure 5.28 Figure 5.29 Figure 5.30 Figure 5.3 1 Figure 5.32 Figure 5.33 Figure 5.34 Figure 6.1 Figure 6.2 Figure 6.3 Figure 6.4 Figure 6.5 Figure 6.6 Figure 6.7 Figure 6.8 Figure 6.9 Figure 6.10 Figure 6.11
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Shape invariance in wrist tangential velocity ..... 124 Acceleration and deceleration in aiming tasks ..... 126 VITE (Vector Integration to Endpoint) model..... 129 Velocity profiles from the VI'IE model ............130 Jordan network for inverse kinematics ............ 132 Learned location sequences for manipulator ...... 134 Massone & Bizzi computational model ........... 136 Generalization capability of model .................137 Double target experiment ............................ 138 Kawato et a1. learning model........................ 139 Wrist velocity and aperture vs. distance ........... 143 Movement time for stationary or moving objects . 149 Aperture for normal and prosthetic hands......... 150 Finger and thumb adjustments during pinch...... 153 Mechanical perturbation to pull arm backwards .. 158 Perturbation of object direction ..................... 160 Perturbation of object size ........................... 164 Grasping with pad and palm opposition ........... 168 Peak aperture and dowel size: pad and palm ...... 170 Peak aperture and dowel size: palm, pad and W 172 Neural pathways during hand movements ........ 176 Kinematics for normal or peripheral vision ....... 180 Dowel size for normal or peripheral vision........ 181 Kinematics for normal or central vision ...........182 Patient grasping without sensory feedback........ 186 Ballpark for placing mug on table ..................188 Schema model for preshape and enclose.......... 190 EMG activity during preshape and enclose .......193 Palm-focused model of grasping ................... 195 Ballpark model of grasping ......................... 197 Black box: setting up an opposition space......... 198 208 Structure of hairless skin ............................ Friction: hysteresis and adhesion ................... 212 Sweat beads on palm ................................. 215 Sweat discharge on palm ............................ 217 Sweat, friction and grip .............................. 221 Mechanoreceptors in skin ........................... 223 Characteristics of skin mechanoreceptors ......... 225 Mechanoreceptors in finger joints ..................227 Exploratory procedures (EPs) ...................... 232 Hand about to grasp object: object support........235 Point contact and soft finger contact ...............236
XVi
Figure 6.12 Figure 6.13 Figure 6.14 Figure 6.15 Figure 6.16 Figure 6.17 Figure 6.18 Figure 6.19 Figure 6.20 Figure 6.21 Figure 6.22 Figure 6.23 Figure 6.24 Figure 6.25 Figure 7.1 Figure 7.2 Figure 7.3 Figure 7.4 Figure 7.5 Figure 8.1 Figure 9.1 Figure 9.2 Figure 9.3 Figure A .1 Figure A.2 Figure A.3 Figure A.4 Figure A S Figure B.1 Figure C.l Figure C.2 Figure C.3 Figure C.4 Figure C.5 Figure C.6 Figure C.7 Figure C.8 Figure C.9 Figure D.l FIgure D.2 Figure D.3
THE GRASPINGH A N D
Two soft fingers contacting object .................238 Multijoint finger ...................................... 241 Applied force and cone of friction ..................244 Two fingers and equilibrium ........................ 245 Apparatus for transducing grasping forces ........248 Grip and load forces: weight and texture ..........250 Phases in applying grasping forces ................251 Grasping forces to acquire an object ...............254 Grasping force errors ................................ 257 Performatory and exploratory movements ........ 267 Hand coordinate frame for manipulation ..........270 Cone of friction and task mechanics ............... 275 277 Baton twirling (from Fearing) ...................... Black box: using an opposition space..............280 Phases: an opposition space analysis ..............284 Forces and kinematics over all phases ............. 286 Opposition vector and approach vector ............288 Palm-focused model of grasping ...................291 Contact: using an opposition space.................297 Levels of mapping for humans and robots ........ 320 Black box revisited ................................... 330 Levels of mapping, over phases .................... 340 Triangle strategy revisited ........................... 342 Planes of the body .................................... 350 Upper limb skeleton .................................. 352 Bones and joints of hand and wrist ................353 Descriptions of movement........................... 357 Dermatome mapping of upper limb ................365 Prehensile postures: summary view................372 McCulloch-Pitts neuron vs. leaky integrator...... 385 Input-output connativity ............................ 386 Multilayer connectivity .............................. 387 Recurrent nets that are completely connected .....388 Learning rules ......................................... 390 Generalized delta rule ................................ 393 Binary and distributed encodings...................394 Heteroassociative memory .......................... 396 Heteroassociative memory for grasping ...........398 StanfordJPL hand ................................... 418 Utah/MIT hand ....................................... 419 Belgrade/USC hand .................................. 421
T H E GRASPING H A N D
List of Figures Figure 1.1 Figure 1.2 Figure 1.3 Figure 2.1 Figure 2.2 Figure 2.3 Figure 2.4 Figure 2.5 Figure 2.6 Figure 2.7 Figure 2.8 Figure 2.9 Figure 2.10 Figure 3.1 Figure 3.2 Figure 3.3 Figure 3.4 Figure 3.5 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 4.5 Figure 4.6 Figure 4.7 Figure 4.8 Figure 4.9 Figure 4.10 Figure 4.1 1 Figure 4.12 Figure 4.13 Figure 4.14 Figure 4.15 Figure 4.16 Figure 4.17 Figure 4.18 Figure 5.1 Figure 5.2 Figure 5.3
Examples of prehension ............................... 5 The prehensile problem ................................ 7 Triangle strategy......................................... 9 Schlesinger classification .............................. 18 Napier classification.................................... 24 Cutkosky and Howe classification ...................26 Various postures ........................................ 28 Prehensile postures as oppositions ..................32 Grasping different sized mugs ........................ 33 Virtual fingers apply oppositions ..................... 34 Jacobson and Sperling coding system ...............38 Virtual finger geometric configuration ...............40 Black box mapping: object, task, postures ..........43 Wrist velocity and hand aperture .................... S O Velocity and aperture: two objects.................... 52 Arbib Coordinated Control Program .................54 Paillard model of reaching and grasping.............55 Greene ballpark model ................................. 56 LAMA robot task plan ................................ 66 Miller et al. TOTE (Test-Operate-Test-Exit) ........68 Three major brain systems ............................ 71 Levels of the CNS ..................................... 73 Paillard model of CNS ................................. 74 Objects viewed in 2D: pinch vs. clench..............78 Opposition vector ....................................... 82 Neural net for object, task, and oppositions ........85 Neural network for objects and oppositions ........88 Results of Uno et al . neural net ....................... 89 Neural network for virtual finger mapping ..........92 Expert system for opposition space ..................93 Kuperstein model for hand-eye coordination .......96 Iberall approach vector neural network ..............99 Iberall approach vector simulations ................100 Rosenbaum et a1. Orienting wrist for tasks........ 102 Stelmach et al. Orienting opposition space ........104 Approach vector ...................................... 106 Coordinated Control Program motor schemas.... 110 Homunculus in motor cortex........................ 113 Computational model of movement ................116
List of Figures Figure 5.4 Figure 5.5 Figure 5.6 Figure 5.7 Figure 5.8 Figure 5.9 Figure 5.10 Figure 5.11 Figure 5.12 Figure 5.13 Figure 5.14 Figure 5.15 Figure 5.16 Figure 5.17 Figure 5.18 Fiiure 5.19 Figure 5.20 Figure 5.21 Figure 5.22 Figure 5.23 Figure 5.24 Figure 5.25 Figure 5.26 Figure 5.27 Figure 5.28 Figure 5.29 Figure 5.30 Figure 5.3 1 Figure 5.32 Figure 5.33 Figure 5.34 Figure 6.1 Figure 6.2 Figure 6.3 Figure 6.4 Figure 6.5 Figure 6.6 Figure 6.7 Figure 6.8 Figure 6.9 Figure 6.10 Figure 6.11
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Shape invariance in wrist tangential velocity ..... 124 Acceleration and deceleration in aiming tasks ..... 126 VITE (Vector Integration to Endpoint) model..... 129 Velocity profiles from the VI'IE model ............130 Jordan network for inverse kinematics ............ 132 Learned location sequences for manipulator ...... 134 Massone & Bizzi computational model ........... 136 Generalization capability of model .................137 Double target experiment ............................ 138 Kawato et a1. learning model........................ 139 Wrist velocity and aperture vs. distance ........... 143 Movement time for stationary or moving objects . 149 Aperture for normal and prosthetic hands......... 150 Finger and thumb adjustments during pinch...... 153 Mechanical perturbation to pull arm backwards .. 158 Perturbation of object direction ..................... 160 Perturbation of object size ........................... 164 Grasping with pad and palm opposition ........... 168 Peak aperture and dowel size: pad and palm ...... 170 Peak aperture and dowel size: palm, pad and W 172 Neural pathways during hand movements ........ 176 Kinematics for normal or peripheral vision ....... 180 Dowel size for normal or peripheral vision........ 181 Kinematics for normal or central vision ...........182 Patient grasping without sensory feedback........ 186 Ballpark for placing mug on table ..................188 Schema model for preshape and enclose.......... 190 EMG activity during preshape and enclose .......193 Palm-focused model of grasping ................... 195 Ballpark model of grasping ......................... 197 Black box: setting up an opposition space......... 198 208 Structure of hairless skin ............................ Friction: hysteresis and adhesion ................... 212 Sweat beads on palm ................................. 215 Sweat discharge on palm ............................ 217 Sweat, friction and grip .............................. 221 Mechanoreceptors in skin ........................... 223 Characteristics of skin mechanoreceptors ......... 225 Mechanoreceptors in finger joints ..................227 Exploratory procedures (EPs) ...................... 232 Hand about to grasp object: object support........235 Point contact and soft finger contact ...............236
XVi
Figure 6.12 Figure 6.13 Figure 6.14 Figure 6.15 Figure 6.16 Figure 6.17 Figure 6.18 Figure 6.19 Figure 6.20 Figure 6.21 Figure 6.22 Figure 6.23 Figure 6.24 Figure 6.25 Figure 7.1 Figure 7.2 Figure 7.3 Figure 7.4 Figure 7.5 Figure 8.1 Figure 9.1 Figure 9.2 Figure 9.3 Figure A .1 Figure A.2 Figure A.3 Figure A.4 Figure A S Figure B.1 Figure C.l Figure C.2 Figure C.3 Figure C.4 Figure C.5 Figure C.6 Figure C.7 Figure C.8 Figure C.9 Figure D.l FIgure D.2 Figure D.3
THE GRASPINGH A N D
Two soft fingers contacting object .................238 Multijoint finger ...................................... 241 Applied force and cone of friction ..................244 Two fingers and equilibrium ........................ 245 Apparatus for transducing grasping forces ........248 Grip and load forces: weight and texture ..........250 Phases in applying grasping forces ................251 Grasping forces to acquire an object ...............254 Grasping force errors ................................ 257 Performatory and exploratory movements ........ 267 Hand coordinate frame for manipulation ..........270 Cone of friction and task mechanics ............... 275 277 Baton twirling (from Fearing) ...................... Black box: using an opposition space..............280 Phases: an opposition space analysis ..............284 Forces and kinematics over all phases ............. 286 Opposition vector and approach vector ............288 Palm-focused model of grasping ...................291 Contact: using an opposition space.................297 Levels of mapping for humans and robots ........ 320 Black box revisited ................................... 330 Levels of mapping, over phases .................... 340 Triangle strategy revisited ........................... 342 Planes of the body .................................... 350 Upper limb skeleton .................................. 352 Bones and joints of hand and wrist ................353 Descriptions of movement........................... 357 Dermatome mapping of upper limb ................365 Prehensile postures: summary view................372 McCulloch-Pitts neuron vs. leaky integrator...... 385 Input-output connativity ............................ 386 Multilayer connectivity .............................. 387 Recurrent nets that are completely connected .....388 Learning rules ......................................... 390 Generalized delta rule ................................ 393 Binary and distributed encodings...................394 Heteroassociative memory .......................... 396 Heteroassociative memory for grasping ...........398 StanfordJPL hand ................................... 418 Utah/MIT hand ....................................... 419 Belgrade/USC hand .................................. 421