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:
- The TO part is based on the TO software trajOptim developed by M. Kelly, who currently works for Atlas in Boston Dynamics.
- The MPC part is referred to the linear MPC controlller for bipedal robots proposed by P. B. Wieber.
- The robot visulization software is organized by Xiang Meng, which are derived from Introduction to Humanoid Robotics written by S. Kajita et al.
Xiang Meng (Ph.D. student in BIT) - Developer/Maintainer