Optimal path planning for an autonomous articulated vehicle with two trailers. (2018)

• Record Type: Journal Article
• Authors: Mohamed, Amr; Ren, Jing; Lang, Haoxiang; El-Gindy, Moustafa
• Is Part Of: International journal of automation and control. Volume 12:Number 3(2018)
• Page Start: 449
• Page End: 465
• Publication Date: 2018
• Subjects: path planning -- autonomous vehicle -- vehicle with two trailer -- artificial potential field -- APF -- optimal control theory; Automation -- Periodicals; Control theory -- Periodicals; Automatic control -- Periodicals; Robots -- Periodicals; Bionics -- Periodicals; Intelligent control systems -- Periodicals
• Languages: English
• ISSNs: 1740-7516

Abstract

This paper proposed an optimal path planning algorithm for autonomous vehicle with two trailers in autonomous navigation. The proposed algorithm is based on combination of artificial potential field (APF) method and optimal control theory. A linear two-degree-of-freedom vehicle model with both lateral and yaw motion is derived and simulated in MATLAB environment. The optimal control theory is applied to generate an optimal free-obstacle path of the robotic vehicle from a starting point to the goal location. The obstacle-avoidance technique is mathematically modelled using a potential function based on the proposed sigmoid function. The constructed potential field model can achieve an accurate analytic description of objects in three dimensions. Moreover, the proposed model of potential field requires very modest computation at run time. The APF includes both the attractive (the target) and repulsive (the obstacles) potential fields that will control the steering angle of the vehicle so that it can reach to its target location. Several simulations are carried out to check the fidelity of the proposed technique. The illustrated results demonstrate the generated optimal path of autonomous vehicles with consideration of vehicle dynamics constraints, obstacle avoidance and collision free criteria in reaching the goal location.