tutorials_trajOptim_MPC

Overview

A simple and light-weight tutorial for trajectory optimization (TO) and model predictive control (MPC).

Different from the reinforcement learning (RL), TO and MPC are general model-based control methods, especially for legged robots and manipulators.

Independent of any external solver, this repository provides a simple and light-weight Matlab (e.g. 2019b version) tutorial for TO and MPC:

1. The TO part is based on the TO software trajOptim developed by M. Kelly, who currently works for Atlas in Boston Dynamics.
2. The MPC part is referred to the linear MPC controlller for bipedal robots proposed by P. B. Wieber.
3. The robot visulization software is organized by Xiang Meng, which are derived from Introduction to Humanoid Robotics written by S. Kajita et al.

Author

Xiang Meng (Ph.D. student in BIT) - Developer/Maintainer