Page 206 - Human Inspired Dexterity in Robotic Manipulation
P. 206

Index  205


              H                                J
              Hand anatomy, 91–92              Joint capsule, 94
               biological joints, 98–100, 98–100f
               bones and joints, 92–93, 92f    K
               extensor tendons, 94–96, 94f,96f  Kinematics vs. dynamics, 79
               flexor tendons, 94–96, 94f,96f
               joint ligaments, 93–94, 93f     L
               tendon sheaths, 96–97, 97f
                                               Learning
              Hand-and-object system, 153f
                                                 dexterous manipulation, 31–32
              Hand control systems structure, 150–152,
                                                 error-based, 29
                   151f
                                                 reinforcement, 29–30
              Hand dimensions, 17
                                                 sensorimotor, 27–28
               boundary family of, 19–20, 19f
                                                 trial-by-trial, 30–31
              Hand-eye coordination, 53
                                                 use-dependent, 29–30, 47–48
              Hand-force-change model, 68–70
                                               Learning manipulation, 29–31
              Hand-jerk model, 63                interaction between multiple
               minimum, 63–68, 73f,76t,77–78f,      sensorimotor process, 31–32, 31f
                   78–79t
                                                 protocols, 32–48
              Hand manipulation, 150
                                                   data analysis, 34–35
              Hand mass
                                                   experimental results, 38–46, 39f,
               estimation by haptic force, 71f
                                                    43f,45f
               identification, 70–72, 74–75
                                                   model and simulation, 35–37
              Hand models, 12
              Hand-object interactions, 28–29  M
              Haptic force, hand mass estimation by, 71f
                                               Manipulation paths, 189–191, 190f
              Haptic sensation, 56
                                               Manipulation planner
              Haptic simulator, 73
                                                 component connection, 193
              Human hand
                                                   path generation, 194
               anatomy of, 12–14, 13f
                                                   transfer path, 193
               motions of, 14
                                                   transit path, 193
               research, 11
                                                   type2 path, 193
              Human-like reaching movements
                                                 examples, 194–199, 195–199f
               analysis, 76–79
                                                 graph components, 191
               in dynamic environment, 62f,64–65
                                                   initial object placement, 192
               modeling of, 61–62, 62f
                                                   intermediate object placement,
                                                    192–193
              I                                    target object placement, 193
              Interference groups (IF), 33       graph structure, 191, 192f
              Internal representation, 35–36, 43–44  path optimization, 194
               of force scaling, 30–31         Mass model, 4–5, 4f
               of manipulation, 43–46          Master-slave system (MSS), 53, 55, 151
              Interphalangeal (IP) joint, 14     multisensory illusion on, 58–59, 58f
               active movements of, 14         MCP joint. See Metacarpophalangeal
              Intrinsic muscles, 14, 95             (MCP) joint
              Intuitive control, 53            Mechanical impedance, 5
              Intuitiveness, 59                Medicine research, design tools for, 90–91
              Inverse internal models, 29      Memory, sensorimotor learning and, 29–30
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