An Efficient Quadratic Programming Approach to Stabilizing Dynamic Locomotion
نویسندگان
چکیده
We describe a whole-body dynamic walking controller implemented as a compact, convex quadratic program. The controller minimizes an optimal control condition on a simple model of the walking system while respecting the dynamic, input, and contact constraints of the full robot dynamics. By exploiting sparsity and temporal structure in the optimization with an active-set algorithm, we surpass the performance of the best available off-the-shelf solvers and achieve real-time control rates for a 34-DOF humanoid. We describe applications to balancing and walking tasks using the simulated Atlas robot in the DARPA Virtual Robotics Challenge.
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