In this paper, the generation of trajectories of both end-effector and joints for human-like reaching and grasping motions is studied. In reaching movement, the human-like end-effector trajectory is obtained based on the minimum jerk model. A total potential energy criterion is constructed to resolve the kinematic redundancy of human arm in the target position. Gradient Projection Method (GPM) is adopted to trace the human-like end-effector trajectory while minimizing the total potential energy to generate the human-like joint trajectory. In grasping movement, the total potential energy and wrist discomfort are synthesized to resolve the kinematic redundancy of human arm in the target position and orientation. A new planner, Gradient Projection Method based Rapidly-exploring Random Tree (GPM-RRT) algorithm, is proposed to generate the human-like end-effector trajectory by goal biasing and the human-like joint trajectory by minimizing the synthesis of the total potential energy and wrist discomfort. The criteria and algorithm are verified by simulations and experiments.
|Number of pages
|Mechanism and Machine Theory
|Published - Nov 2014
Bibliographical noteFunding Information:
The support of this research by the National Natural Science Foundation of China and Doctoral Fund of Innovation of Beijing University of Technology (No. YB201303 ) are appreciated.
- Human arm redundancy resolution
- Human-like movements
- Optimal sampling-based algorithms
- Robotic arms
ASJC Scopus subject areas
- Mechanics of Materials
- Mechanical Engineering
- Computer Science Applications