This repository contains the implementation of Model-Predictive-Control(MPC) algorithm for path tracking on TurtleBot3 simulator using python, CasADi ipopt solver and ROS framework. Point tracking(self parking) is achieved by using the same target location-orientation while determining cost for each predicted timestep. The solution corresponding to the minimum value of cost function is therefore, the best method to reach the target with respect to the particular gain parameters. The gain parameters can be further adjusted to achieve specific objectives like minimising time taken or limiting acceleration for a smoother ride.
References:
Model predictive control: past, present and future
An Introduction to Model-based Predictive Control (MPC) by Stanislaw H. Żak
Model Predictive Control System Design and Implementation Using MATLAB® by Liuping Wang
Implementation of Model Predictive Control (MPC) and Moving Horizon Estimation (MHE) on Matlab
(The arrow marks the target location and orientation)
