Details

Autor(en) / Beteiligte

• Kuindersma, Scott
• Deits, Robin
• Fallon, Maurice
• Valenzuela, Andrés
• Dai, Hongkai
• Permenter, Frank
• Koolen, Twan
• Marion, Pat
• Tedrake, Russ

Titel

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

Alma/SFX Local Collection

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.