Coupled Dynamical System Based Hand-Arm Grasp Planning under Real-Time Perturbations

Robustness to perturbation has been advocated as a key element to robot control and efforts in that direction are numerous. While in essence these approaches aim at “endowing robots with a flexibility similar to that displayed by humans”, few have actually looked at how humans react in the face of fast perturbations. We recorded the kinematic data from human subjects during grasping motions under very fast perturbations. Results show a strong coupling between the reach and grasp components of the task that enables rapid adaptation of the fingers in coordination with the hand posture when the target object is perturbed. We develop a robot controller based on Coupled Dynamical Systems that exploits coupling between two dynamical systems driving the hand and finger motions. This offers a compact encoding for a variety of reach and grasp motions that adapts on-the-fly to perturbations without the need for any re-planning. To validate the model we control the motion of the iCub robot when reaching for different objects.