Humanoid motion planning for dual-arm manipulation and re-grasping tasks

— In this paper, we present efficient solutions for planning motions of dual-arm manipulation and re-grasping tasks. Motion planning for such tasks on humanoid robots with a high number of degrees of freedom (DoF) requires computationally efficient approaches to determine the robot’s full joint configuration at a given grasping position, i.e. solving the Inverse Kinematics (IK) problem for one or both hands of the robot. In this context, we investigate solving the inverse kinematics problem and motion planning for dual-arm manipulation and re-grasping tasks by combining a gradient-descent approach in the robot’s pre-computed reachability space with random sampling of free parameters. This strategy provides feasible IK solutions at a low computation cost without resorting to iterative methods which could be trapped by joint-limits. We apply this strategy to dual-arm motion planning tasks in which the robot is holding an object with one hand in order to generate whole-body robot...

• Type: Conference
• Year: 2009
• Where: IROS
• Authors: Niko Vahrenkamp, Dmitry Berenson, Tamim Asfour, James Kuffner, Rüdiger Dillmann
• Keywords: Inverse Kinematics, IROS 2009, Motion Planning, Re-grasping Tasks, Robotics