Title: Path planning and tracking for autonomous mining articulated vehicles

Authors: Fengqian Dou; Yanjun Huang; Li Liu; Hong Wang; Yu Meng; Lianqiang Zhao

Addresses: School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, 100083, China ' Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada ' School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, 100083, China ' Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada ' School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, 100083, China; Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing, 100083, China ' Beijing City University, Beijing, 101309, China

Abstract: This paper presents a path planning and tracking framework for autonomous mining articulated vehicles (AVs). The relation space method is proposed for path planning. In this method, a self-organising, competitive neural network is adopted to identify the space around the vehicle. Then, the vehicle's optimal driving direction is determined by using the spatial geometric relationships of the identified space. A proportional-integral-derivative (PID) controller is used to control the vehicle speed, whereas a model predictive control (MPC) is designed for steering control, where the path tracking error model is used for MPC development. In addition, the AV's dynamics model is built in Adams. The effect and sensitivity of the path-tracking controller are validated through the Matlab-Adams co-simulation. The test results show the satisfactory path-tracking performance.

Keywords: articulated vehicle; AV; RSM; relation space method; path planning and tracking; MPC; model predictive control.

DOI: 10.1504/IJHVS.2019.101475

International Journal of Heavy Vehicle Systems, 2019 Vol.26 No.3/4, pp.315 - 333

Received: 19 Jan 2017
Accepted: 20 Sep 2017
Published online: 11 Aug 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article