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Modeling, system identication, and control for dynamic locomotion of the LittleDog robot on rough terrain

Author(s)
Levashov, Michael Yurievich
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Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.
Advisor
Russ L. Tedrake.
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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
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Abstract
In this thesis, I present a framework for achieving a stable bounding gait on the LittleDog robot over rough terrain. The framework relies on an accurate planar model of the dynamics, which I assembled from a model of the motors, a rigid body model, and a novel physically-inspired ground interaction model, and then identied using a series of physical measurements and experiments. I then used the RG-RRT algorithm on the model to generate bounding trajectories of LittleDog over a number of sets of rough terrain in simulation. Despite signicant research in the field, there has been little success in combining motion planning and feedback control for a problem that is as kinematically and dynamically challenging as LittleDog. I have constructed a controller based on transverse linearization and used it to stabilize the planned LittleDog trajectories in simulation. The resulting controller reliably stabilized the planned bounding motions and was relatively robust to signicant amounts of time delays in estimation, process and estimation noise, as well as small model errors. In order to estimate the state of the system in real time, I modified the EKF algorithm to compensate for varying delays between the sensors. The EKF-based filter works reasonably well, but when combined with feedback control, simulated delays, and the model it produces unstable behavior, which I was not able to correct. However, the close loop simulation closely resembles the behavior of the control and estimation on the real robot, including the failure modes, which suggests that improving the feedback loop might result in bounding on the real LittleDog. The control framework and many of the methods developed in this thesis are applicable to other walking systems, particularly when operating in the underactuated regime.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.
 
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 (p. 76-80).
 
Date issued
2012
URI
http://hdl.handle.net/1721.1/71273
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Publisher
Massachusetts Institute of Technology
Keywords
Aeronautics and Astronautics.

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