To achieve agile running of a biped robot, dynamic stability, joint coordination, and real-time ability are required. In this paper, a task-space-based controller framework is constructed with a reduced-order 3D-SLIP model. On the top layer, a 3D-SLIP model based planner is employed for center-of-mass trajectory planning. The planner built with optimization for table divided apex state, and a neural network is used to fit the optimized table for real-time planning. On the bottom layer, a task-space-based controller with full-body dynamics is utilized, which solves the quadratic programming for the optimized joint torque in real-time. A 12-DOF biped robot model with a point-foot is used for simulation verification. The simulation result show that stable running and single-cycle apex state change running can achieved with the framework.
