DOI: 10.3390/s24010221 ISSN: 1424-8220

An Integrated Autonomous Dynamic Navigation Approach toward a Composite Air–Ground Risk Construction Scenario

Da Jiang, Meijing Wang, Xiaole Chen, Hongchao Zhang, Kang Wang, Chengchi Li, Shuhui Li, Ling Du
  • Electrical and Electronic Engineering
  • Biochemistry
  • Instrumentation
  • Atomic and Molecular Physics, and Optics
  • Analytical Chemistry

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.

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