This paper presents a real-time and deterministic path planning method for autonomous ships or Unmanned Surface Vehicles (USV) in complex and dynamic navigation environments. A modified Artificial Potential Field (APF), which contains a new modified repulsion potential field function and the corresponding virtual forces, is developed to address the issue of Collision Avoidance (CA) with dynamic targets and static obstacles, including emergency situations. Appropriate functional and safety requirements are added in the corresponding virtual forces to ensure International Regulations for Preventing Collisions at Sea (COLREGS)-constrained behaviour for the own ship's CA actions. Simulations show that the method is fast, effective and deterministic for path planning in complex situations with multiple moving target ships and stationary obstacles and can account for the unpredictable strategies of other ships. The authors believe that automatic navigation systems operated without human interaction could benefit from the development of path planning algorithms.

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A new potential field method for mobile robot path planning is proposed in this paper. At present, most potential field methods are designed to be applied in the stationary environment, and several improved potential functions have brought in the velocity factors in the dynamic circumstances. Based on the consideration that the moving trend of the robot in the dynamic environments is also necessary to produce more reasonable path, this paper defines new attractive potential function with respect to the relative position, velocity, and acceleration between the robot and the goal, as well as the repulsive potential function with respect to the relative positions, velocities, and accelerations between the robot and the obstacles. The virtual forces are calculated to make the robot plan its motion, not only with right positions, but also with suitable velocities. Furthermore, the robot will keep a similar moving trend with the goal and contrary trends with the obstacles. Finally, some methodic simulations are carried out to validate and demonstrate the effectiveness of the new potential field method.

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