This paper addresses the problem of designing a planning algorithm for anthropomorphic dual-arm robotic systems to find paths that mimics the movements of real human beings by using first-order synergies (correlations between joint velocities). The key idea of the proposal is to convert captured human movements into a vector field of velocities, defined in the configuration space of the robot, and use it to guide the search of a solution path. The motion planning is solved using the proposed algorithm, called FOS-BKPIECE, that is a bidirectional version of the KPIECE planner working with an improved version of the extension procedure of the VF-RRT planner. The obtained robot movements follow the directions of the defined vector field and hence allow the robot to solve the task in a human-like fashion. The paper presents a description of the proposed approach as well as results from conceptual and application examples, the latter using a real anthropomorphic dual-arm robotic system. A thorough comparison with other previous planning algorithms shows that the proposed approach obtains better results. ; Postprint (published version)
First-order synergies for motion planning of anthropomorphic dual-arm robots
2017-07-01
Article (Journal)
Electronic Resource
English
DDC: | 629 |
Task-dependent synergies for motion planning of an anthropomorphic dual-arm system
BASE | 2017
|Anthropomorphic robots for nonverbal communication
British Library Online Contents | 1997
|Including virtual constraints in motion planning for anthropomorphic hands
BASE | 2011
|Including virtual constraints in motion planning for anthropomorphic hands
BASE | 2011
|