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.
United States. Air Force Office of Scientific Research (FA8750-12-1-0321)
United States. Office of Naval Research (N00014-12-1-0071)
United States. Office of Naval Research (N00014-10-1-0951)
National Science Foundation (U.S.) (IIS-0746194)
National Science Foundation (U.S.) (IIS-1161909)