Grasp Planning Based on Grasp Strategy Extraction from Demonstration
thumb, robots, joints, planning, wrist, kinematics, optimization, robotic grasp planning, Shadow hand, Barrett hand, robotic hand, search space, wrist position constraints, hand posture constraints, kinematic correspondence problem, grasp strategy representation, task property representation, human grasping, force-closure-based grasp planning procedure, object grasping, relative thumb orientations, relative thumb positions, grasp type, grasp intention
Digital Object Identifier (DOI)
In this paper, we discuss information that is beneficial to robotic grasp planning and can be extracted from human demonstration. We present a method that integrates grasp intention: grasp type, and the relative thumb positions and orientations on the grasped object to the force-closure-based grasp planning procedure. Instead of completely mimicking the human grasp, grasp type and the relative thumb position are partially extracted from the demonstration to represent the task properties and grasp strategies, and avoid the challenging kinematic correspondence problem. Instead of mapping the demonstrated motion, the grasp type and thumb position provide meaningful constraints on hand posture and wrist position. Both the feasible workspace of a robotic hand and the search space of grasp planning are thereby highly reduced by the constraints. This approach has been evaluated in a simulation with a Barrett hand and a Shadow hand on eight daily objects.
Was this content written or created while at USF?
Citation / Publisher Attribution
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, p. 4458-4463.
Scholar Commons Citation
Lin, Yun and Sun, Yu, "Grasp Planning Based on Grasp Strategy Extraction from Demonstration" (2014). Computer Science and Engineering Faculty Publications. 77.