Chapter 2. Prehension

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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
THE GRASPING HAND
List of Figures
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 .................... SO
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