Balance control and locomotion planning for humanoid robots using nonlinear centroidal models
Author(s)Koolen, Frans Anton.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
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Balance control approaches for humanoid robots have traditionally relied on low-dimensional models for locomotion planning and reactive balance control. Results for the low-dimensional model are mapped to the full robot, and used as inputs to a whole-body controller. In particular, the linear inverted pendulum (LIP) has long been the de facto standard low-dimensional model used in balance control. The LIP has its limitations, however. For example, it requires that the robot's center of mass move on a plane and that the robot's contact environment be planar. This thesis presents control and planning approaches using nonlinear low-dimensional models, aimed at mitigating some of the limitations of the LIP. Specically, the contributions are: 1) a closed-form controller and region of attraction analysis for a nonlinear variable-height inverted pendulum model, 2) a trajectory optimization approach for humanoid robot locomotion over moderately complex terrain based on mixed-integer nonlinear programming with a low-dimensional model, and 3) a quadratic-programming based controller that uses the the results from these low-dimensional models to control a simulation model of the Atlas humanoid robot.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2020Cataloged from student-submitted PDF of thesis.Includes bibliographical references (pages 133-151).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.