Title: Comparative study of dynamic programming and Pontryagin's minimum principle for autonomous multi-wheeled combat vehicle path planning

Authors: Amr Mohamed; Jing Ren; Xishi Huang; A.N. Ouda; G.M. Abdo

Addresses: Faculty of Engineering and Applied Science, University of Ontario Institute of Technology (UOIT), Oshawa, ON, L1G 0C5, Canada ' Faculty of Engineering and Applied Science, University of Ontario Institute of Technology (UOIT), Oshawa, ON, L1G 0C5, Canada ' Istuary Innovation Group, 75 Tiverton Court, Markham, ON, l3r 4m8, Canada ' Faculty of Engineering and Applied Science, University of Ontario Institute of Technology (UOIT), Oshawa, ON, L1G 0C5, Canada ' Faculty of Engineering and Technology, Department of Mechanical Engineering, Badr University, Cairo, Egypt

Abstract: This paper presents a comparative study of two path planning algorithms using optimal control theory for the autonomous multi-wheeled combat vehicle. The developed optimal path planning algorithms use Pontryagin's minimum principle (PMP) and dynamic programming (DP) approaches. PMP and DP are two major branches of the optimal control theory. A simplified two degrees of freedom (DOF) vehicle model is used to derive the differential equations of the vehicle. The cost function associated with the path generation is to be minimised with the vehicle dynamics equations. A comparative study and performance analysis of generated optimal paths using the proposed algorithms was carried out for various scenarios. The simulation results demonstrate that the generated optimal solution using PMP is very close to the DP solution, which is the guaranteed global optimum. In addition, the initial and final condition parameters and the vehicle dynamics are satisfied. However, the PMP computation time is significantly less than the DP.

Keywords: path planning; dynamic programming; autonomous vehicle; PMP; Pontryagin's minimum principle.

DOI: 10.1504/IJHVS.2019.101498

International Journal of Heavy Vehicle Systems, 2019 Vol.26 No.3/4, pp.565 - 577

Received: 24 Sep 2018
Accepted: 25 Sep 2018
Published online: 11 Aug 2019 *

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