Bio-inspired algorithms for tactile control of dexterous manipulation

Few years old children lift and manipulate unfamiliar objects more dexterously than today's robots. Thus, robotics researchers increasingly agree that ideas from biology can strongly benefit the design of autonomous robots. In this paper, bio-inspired algorithms for lifting unfamiliar objects with grasp stability and human-like behavior are presented. In these algorithms, simulated human tactile afferent responses, drive the control of the grip and load forces, and signal important events in the lifting task. The presented model and algorithms follow closely the human behavior in a lifting task, as revealed by neurophysiological studies of human dexterous manipulation.