Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain

Thesis: Sc. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.

Bibliographic Details
Main Author: Valenzuela, Andrés Klee
Other Authors: Russ Tedrake.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2016
Subjects:
Online Access:http://hdl.handle.net/1721.1/103432
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author Valenzuela, Andrés Klee
author2 Russ Tedrake.
author_facet Russ Tedrake.
Valenzuela, Andrés Klee
author_sort Valenzuela, Andrés Klee
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description Thesis: Sc. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.
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spelling mit-1721.1/1034322019-04-11T14:23:22Z Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain Valenzuela, Andrés Klee Russ Tedrake. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering. Mechanical Engineering. Thesis: Sc. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (pages 79-84). Planning dynamic motions for a legged robot entails addressing both the continuous question of how its joints should move and the combinatorial question of which hand or foot should touch which surface and in what order. Fortunately, these two questions are linked by the centroidal dynamics of the robot, which we can express either in terms of its joint angle trajectories or in terms of its foot placements and applied forces. Based on this insight, I formulate a pair of mathematical programs for planning highly dynamic motions for legged robots. The first is a mixed-integer convex program, specifically, a mixed-integer quadratic program (MIQP), that yields a sequence of footholds/handholds as well as center of mass (COM) and angular momentum trajectories. The second is a trajectory optimization, formulated as a nonlinear program (NLP), that returns trajectories for the COM, angular momentum, and joint angles subject to the footholds/handholds chosen by the MIQP step. While any number of trajectory optimization schemes could be used here, we present one which is particularly useful in this case, as it enforces the system's dynamics directly in terms of its COM motion and angular momentum. As a result, the solution to the MIQP provides constraints (where each end-effector is required to make contact with the environment) for the NLP and also gives seeds for the decision variables corresponding to the robot's centroidal motion. Thus, the three primary contributions of this thesis are: an MIQP-based approach to gait selection over irregular terrain, a trajectory optimization formulation for floating-base systems subject to external forces and kinematic constraints, and a planning methodology that integrates both of those to generate highly dynamic motions in challenging environments. I apply these techniques to models of a quadruped and a humanoid (Boston Dynamics' LittleDog and Atlas respectively) to generate motion plans for running, jumping, and other dynamic behaviors. by Andrés Klee Valenzuela. Sc. D. 2016-07-01T18:23:33Z 2016-07-01T18:23:33Z 2016 2016 Thesis http://hdl.handle.net/1721.1/103432 952334378 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 84 pages application/pdf Massachusetts Institute of Technology
spellingShingle Mechanical Engineering.
Valenzuela, Andrés Klee
Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain
title Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain
title_full Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain
title_fullStr Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain
title_full_unstemmed Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain
title_short Mixed-integer convex optimization for planning aggressive motions of legged robots over rough terrain
title_sort mixed integer convex optimization for planning aggressive motions of legged robots over rough terrain
topic Mechanical Engineering.
url http://hdl.handle.net/1721.1/103432
work_keys_str_mv AT valenzuelaandresklee mixedintegerconvexoptimizationforplanningaggressivemotionsofleggedrobotsoverroughterrain