Effect of kinematic parameters on MPC based on-line motion planning for an articulated vehicle

Abstract

The aim of this article is to analyze the effect of kinematic parameters on a novel proposed on-line motion planning algorithm for an articulated vehicle based on Model Predictive Control. The kinematic parameters that are going to be investigated are the vehicle's velocity, the maximum allowable change in the articulated steering angle, the safety distance from the obstacles and the total number of obstacles in the operating arena. The proposed modified path planning algorithm for the articulated vehicle belongs to the family of Bug-Like algorithms and is able to take under consideration, the mechanical and physical constraints of the articulated vehicle, as well as its full kinematic model. During the on-line motion planning algorithm, the MPC controller controls the lateral motion of the vehicle, through the rate of the articulation angle, while driving it accurately and safely over the on-line formulated desired path. The efficiency of the proposed combined path planning and control scheme is being evaluated under numerous simulated test cases, while exhaustive simulations have been made for analyzing the dependency of the proposed framework on the kinematic parameters.

Obstacle Avoidance of Semi-Trailers Based on Nonlinear Model Predictive Control

“…Combining (10) and (12), the obstacle avoidance model of the semi-trailer can be abbreviated as . The obstacle avoidance model of the trailer Figure 6.…”

“…Gong et al designed an MPC-based obstacle avoidance method based on the penalty function [9]. Nayl et al proposed an MPC-based obstacle avoidance method for an articulated vehicle [10]. Wang three-dimensional space [11].…”

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“…Nayl et al [18] proposed a sliding mode controller based on a novel continuous sliding surface and the nonlinear kinematic equations, being applied to the case of a LHD vehicle. They also analyzed the effect of kinematic parameters on model predictive controller (MPC) using a simulated LHD model in [19]. Alshaer et al [20], [21] modeled the wheel loader as a multi-body mechanical system and applied the model to track the desired path with a fuzzy logic controller and a proportional integral derivative (PID) controller.…”

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“…Therefore, automated UAVs (AUAVs) have first priority in underground mines. However, the automation of their precise control and navigation requires related information on the target vehicle [4][5][6], which includes the attitude, velocities, and even accelerations relative to different directions [7].…”