Affiliation:
1. National Engineering Laboratory for Wheeled Vehicle, China North Vehicle Research Institute, Beijing 100072, China
2. School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Abstract
Unmanned transportation in construction scenarios presents a significant challenge due to the presence of complex dynamic on-ground obstacles and potential airborne falling objects. Consequently, the typical methodology for composite air–ground risk avoidance in construction scenarios holds enormous importance. In this paper, an integrated potential-field-based risk assessment approach is proposed to evaluate the threat severity of the environmental obstacles. Meanwhile, the self-adaptive dynamic window approach is suggested to manage the real-time motion planning solution for air–ground risks. By designing the multi-objective velocity sample window, we constrain the vehicle’s speed planning instructions within reasonable limits. Combined with a hierarchical decision-making mechanism, this approach achieves effective obstacle avoidance with multiple drive modes. Simulation results demonstrate that, in comparison with the traditional dynamic window approach, the proposed method offers enhanced stability and efficiency in risk avoidance, underlining its notable safety and effectiveness.
Funder
Central Military Commission Science and Technology Commission Project
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
1 articles.
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