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Hybrid Path Planning for Unmanned Surface Vehicles in Inland Rivers Based on Collision Avoidance Regulations.

Pengcheng Gao1, Pengfei Xu1, Hongxia Cheng1

  • 1College of Harbor, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China.

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Summary
This summary is machine-generated.

This study presents a hybrid path planning method for unmanned surface vehicles in inland rivers. The approach enhances autonomous navigation safety and efficiency by combining improved A* and model predictive control algorithms.

Keywords:
collision avoidance regulations in inland rivershybrid path planningimproved A* algorithmimproved model predictive control algorithmunmanned surface vehicle in inland rivers

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Area of Science:

  • Robotics and Autonomous Systems
  • Naval Architecture and Marine Engineering
  • Intelligent Transportation Systems

Background:

  • Increasing use of unmanned surface vehicles (USVs) in inland waterways, particularly the Yangtze River.
  • Need for robust autonomous navigation systems to handle complex riverine environments.
  • Advancements in intelligent waterway systems necessitate sophisticated path planning.

Purpose of the Study:

  • To propose a hybrid path planning method for the "Jinghai-I" USV in inland rivers.
  • To enhance global path optimization and local path planning for collision avoidance.
  • To improve the accuracy and safety of autonomous navigation in complex riverine conditions.

Main Methods:

  • Improved A* algorithm with a refined heuristic function and added constraints (channel boundaries, courses).
  • Path smoothing to comply with inland river collision avoidance regulations.
  • Improved Model Predictive Control (MPC) incorporating path-deviation cost, yaw angle constraints, and scenario-specific collision avoidance parameters.

Main Results:

  • Successfully minimized path-tracking error through MPC adjustments.
  • Enhanced the rationality of local path planning by considering navigation rules and encounter scenarios.
  • Demonstrated effectiveness via simulation experiments mimicking real-world navigation conditions.

Conclusions:

  • The hybrid path planning method effectively addresses the challenges of USV navigation in inland rivers.
  • The integration of improved A* and MPC offers a robust solution for autonomous navigation.
  • The proposed approach enhances safety, efficiency, and compliance with navigation regulations.