@article {Kuindersma16,
	title = {Optimization-based locomotion planning, estimation, and control design for Atlas},
	journal = {Autonomous Robots},
	volume = {40},
	number = {3},
	year = {2016},
	note = {
	Winner of the IEEE-RAS Technical Commmittee on Whole-Body Control 2016 Best Paper of the Year Award



	\&nbsp;



	[[{"fid":"3193196","view_mode":"default","type":"media","attributes":{"height":"360","width":"480","alt":"Egress Robustness Tests on YouTube","title":"Egress Robustness Tests","class":"media-element file-default"}}]]



	[[{"fid":"3193216","view_mode":"default","type":"media","attributes":{"height":"360","width":"480","alt":"Atlas walking, running, and jumping in simulation on YouTube","title":"Atlas walking, running, and jumping in simulation","class":"media-element file-default"}}]]

},
	pages = {429{\textendash}455},
	abstract = {
	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.

},
	doi = {10.1007/s10514-015-9479-3},
	author = {Scott Kuindersma and Deits, Robin and Fallon, Maurice and Valenzuela, Andr{\'e}s and Dai, Hongkai and Frank Permenter and Koolen, Twan and Marion, Pat and Russ Tedrake}
}
