Self-protective whole body motion for humanoid robots based on synergy of global reaction and local reflex
This paper describes a self-protective whole body motor controller to enable life-long learning of humanoid robots. In order to reduce the damages on robots caused by physical interaction such as obstacle collision, we introduce self-protective behaviors based on the adaptive coordination of full-body global reactions and local limb reflexes. Global reactions aim at adaptive whole-body movements to prepare for harmful situations. The system incrementally learns a more effective association of the states and global reactions. Local reflexes based on a force-torque sensing function to reduce the impact load on the limbs independently of high-level motor intention. We examined the proposed method with a robot simulator in various conditions. We then applied the systems on a real humanoid robot.
humanoid robot reflex physical interaction incremental learning force detection