Abstract
The plantar area of the human foot is larger than that of quadrupeds' foot, and it contains a large number of sensory organs. Thus, such a foot structure plays a crucial role in extracting "rich" sensory information for the generation of adaptive walking in humans. Here, we propose novel central pattern generator (CPG)-based control of a bipedal walking robot by exploiting plantar sensation. To effectively exploit plantar sensory information, we redesign the local sensory feedback to the CPG model that we previously proposed for quadruped robots. The simulation results indicate that the biped model exhibits a remarkably robust walking ability by exploiting the plantar sensation according to the current walking motion.