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Ch. 10 - Trajectory Optimization

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© Russ Tedrake, 2024 Last modified 2024-11-11. How to cite these notes, use annotations, and give feedback. Note: These are working notes used for a course being taught at MIT. They will be updated throughout the Spring 2024 semester. Lecture videos are available on YouTube. I've argued that optimal control is a powerful framework for specifying complex behaviors with simple objective functions, letting the dynamics and constraints on the system shape the resulting feedback controller (and vice versa!). But the computational tools that we've provided so far have been limited in some important ways. The numerical approaches to dynamic programming which involve putting a mesh over the state space do not scale well to systems with state dimension more than four or five. Linearization around a nominal operating point (or trajectory) allowed us to solve for locally optimal control policies (e.g. using LQR) for even very high-dimensional systems, but the effectiveness of the resulting contro

Ch. 10 - Trajectory Optimization Note: These are working notes used for a course being taught at MIT . They will be updated throughout the Spring 2024 semester. Lecture videos are available on YouTube . Previous Chapter Table of contents Next Chapter Trajectory Optimization I've argued that optimal control is a powerful framework for specifying complex behaviors with simple objective functions, letting the dynamics and constraints on the system shape the resulting feedback controller (and vice versa!). But the computational tools that we've provided so far have been limited in some important w

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