Biomimetic grasp planning for cortical control of a robotic hand

— In this paper we outline a grasp planning system designed to augment the cortical control of a prosthetic arm and hand. A key aspect of this task is the presence of on-line user input, which will ultimately be obtained by identifying and extracting the relevant signals from brain activity. Our grasping system can combine partial or noisy user input and autonomous planning to enable the robot to perform stable grasping tasks. We use principal component analysis applied to the observed kinematics of physiologic grasping to reduce the dimensionality of hand posture space and simplify the planning task for on-line use. The planner then accepts control input in this reduced-dimensionality space, and uses it as a seed for a hand posture optimization algorithm based on simulated annealing. We present two applications of this algorithm, using data collected from both primate and human subjects during grasping, to demonstrate its ability to synthesize stable grasps using partial control inp...

• Type: Conference
• Year: 2008
• Where: IROS
• Authors: Matei T. Ciocarlie, Samuel T. Clanton, M. Chance Spalding, Peter K. Allen
• Keywords: Cortical Control, Grasping, IROS 2008, Robotics, Stable Grasping Tasks