Kinematic Redundancy Resolution for Humanoid Robots by Human Motion Database
IEEE Robotics and Automation Letters (RA-L), vol. 5, no. 4, pp. 6948-6955, 2020
In this letter, we present a method for resolving kinematic redundancy using a human motion database, with application to teleoperation of bimanual humanoid robots using low-cost devices. Handheld devices for virtual reality applications can realize low-cost interfaces for operating such robots but available information does not uniquely determine the arm configuration. The resulting arm motions may be unnatural and inconsistent due to the kinematic redundancy. The idea explored in this paper is to construct a human motion database in advance using an interface that can directly measure the whole arm configuration such as motion capture. During teleoperation, the database is used to infer the appropriate arm configuration, grasp forces, and object trajectory based on the end effector trajectories measured by low-cost devices. The database employs Bayesian Interaction Primitives that have been used for modeling human-robot interactions.