Learning and synchronization of movement primitives for bimanual manipulation tasks

Bimanual manipulation tasks require strong coordination between the two hands performing the task. Trajectories of both arms must be temporally synchronized while satisfying certain spatial constraints while performing the task. In this paper, control laws for the desired trajectory tracking and synchronization of multiple agents modeled using dynamic movement primitives (DMPs) are developed. The control laws are developed using contraction analysis of nonlinear systems. Specific control laws and tracking and synchronization constraints for bimanual tasks are developed. Experimental results suggest that the proposed control laws are robust to spatial perturbations and on-the fly goal location changes.