Sparsely extracting stored movements to construct interfaces for humanoid end-effector control


This paper proposes a robot interface design method by which we can control humanoid end-effector movements with such a low-dimensional input device as a gamepad. In our proposed method, first, the numbers of movement trajectories to accomplish different tasks are generated using a simulated robot model and stored in a database. Second, a human user demonstrates the current task-related behavior. Third, the corresponding stored movements for the demonstrated human behavior are sparsely extracted by a sparse coding method. Finally, the sparsely extracted movement bases are linearly combined to generate a novel movement to accomplish a new target task where the linear weight parameters are modulated by the gamepad. We easily generated such complicated hand movements as spiral motions on a small humanoid robot with our proposed interface.

Proceedings of the 2015 IEEE Conference on Robotics and Biomimetics