Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot

  title={Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot},
  author={Scott Kuindersma and Robin Deits and Maurice F. Fallon and Andres Valenzuela and Hongkai Dai and Frank Permenter and Twan Koolen and Pat Marion and Russ Tedrake},
  journal={Auton. Robots},
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… CONTINUE READING
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Active set vs. interior point strategies for model predictive control

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  • Proceedings of the American Control Conference…
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