Balance control and locomotion planning for humanoid robots using nonlinear centroidal models

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).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.by Frans Anton Koolen.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienc