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Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
Ist Teil von
Autonomous robots, 2016-03, Vol.40 (3), p.429-455
Ort / Verlag
New York: Springer US
Erscheinungsjahr
2016
Link zum Volltext
Quelle
Springer
Beschreibungen/Notizen
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.