Optimization based locomotion planning, estimation, and control design for the atlas humanoid robot
This paper describes a collection of optimization algorithms for achieving dynamic planning, control, and state estimation for a bipedal robot designed to operate reliably in complex environments. To make challenging locomotion tasks tractable, we describe several novel applications of convex, mixed integer, and sparse nonlinear optimization to problems ranging from footstep placement to whole body planning and control. We also present a state estimator formulation that, when combined with our walking controller, permits highly precise execution of extended walking plans over non flat terrain. We describe our complete system integration and experiments carried out on Atlas, a full size hydraulic humanoid robot built by Boston Dynamics, Inc.
Auton. Robots