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...

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Published in:Autonomous robots 2016-03, Vol.40 (3), p.429-455
Main Authors: Kuindersma, Scott, Deits, Robin, Fallon, Maurice, Valenzuela, Andrés, Dai, Hongkai, Permenter, Frank, Koolen, Twan, Marion, Pat, Tedrake, Russ
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Computer Imaging
Control
Engineering
Humanoid
Locomotion
Mechatronics
Optimization
Pattern Recognition and Graphics
Planning
Robotics
Robotics and Automation
Robots
State estimation
Task complexity
Vision
Walking
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cited_by cdi_FETCH-LOGICAL-c495t-976a3626c9031147082162dbc4b4bf5cfed6bc76ddd9ae6ecf1009ab738065563
cites cdi_FETCH-LOGICAL-c495t-976a3626c9031147082162dbc4b4bf5cfed6bc76ddd9ae6ecf1009ab738065563
container_end_page 455
container_issue 3
container_start_page 429
container_title Autonomous robots
container_volume 40
creator Kuindersma, Scott
Deits, Robin
Fallon, Maurice
Valenzuela, Andrés
Dai, Hongkai
Permenter, Frank
Koolen, Twan
Marion, Pat
Tedrake, Russ
description 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_str_mv 10.1007/s10514-015-9479-3
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subjects Algorithms
Artificial Intelligence
Computer Imaging
Control
Engineering
Humanoid
Locomotion
Mechatronics
Optimization
Pattern Recognition and Graphics
Planning
Robotics
Robotics and Automation
Robots
State estimation
Task complexity
Vision
Walking
title Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot
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