Abstract
Focusing on the collision avoidance problem for Unmanned Surface Vehicles (USVs) in the scenario of multi-vessel encounters, a USV autonomous obstacle avoidance algorithm based on the improved velocity obstacle method is proposed. The algorithm is composed of two parts: a multi-vessel encounter collision detection model and a path re-planning algorithm. The multi-vessel encounter collision detection model draws on the idea of the velocity obstacle method through the integration of characteristics such as the USV dynamic model in the marine environment, the encountering vessel motion model, and the International Regulations for Preventing Collisions at Sea (COLREGS) to obtain the velocity obstacle region in the scenario of USV and multi-vessel encounters. On this basis, two constraint conditions for the motion state space of USV obstacle avoidance behavior and the velocity obstacle region are added to the dynamic window algorithm to complete a USV collision risk assessment and generate a collision avoidance strategy set. The path re-planning algorithm is based on the premise of the minimum resource cost and uses an improved particle swarm algorithm to obtain the optimal USV control strategy in the collision avoidance strategy set and complete USV path re-planning. Simulation results show that the algorithm can enable USVs to safely evade multiple short-range dynamic targets under COLREGS.
Highlights
Unmanned Surface Vehicles (USVs) have broad application prospects in marine environmental monitoring, marine rights and interests maintenance, and military fields and have become a research hotspot in the field of marine intelligent equipment [1,2,3,4]
The above model construction process is completed in an ideal state, ignoring COLUSV dynamic characteristics in the marine environment, and 10 theof encountering vessel motion characteristics; this paper comprehensively considers the constraints of the above factors to construct the multi-vessel encounter collision detection model
Through an experimental comparison with the USV autonomous obstacle avoidance algorithm based on velocity obstacle (VO) and the USV autonomous obstacle avoidance algorithm based on SBG, the performance of the proposed USV autonomous obstacle avoidance algorithm based on improved VO was further analyzed to verify the security, timeliness, and economy of the algorithm
Summary
Unmanned Surface Vehicles (USVs) have broad application prospects in marine environmental monitoring, marine rights and interests maintenance, and military fields and have become a research hotspot in the field of marine intelligent equipment [1,2,3,4]. The authors of [25] use the Monte Carlo method to set ship navigation safety rules in a distributed form based on constructing the probabilistic velocity obstacle region; USV can determine the timing and priority of triggering a collision avoidance strategy according to this rule This method does not consider COLREGS constraint conditions and the dynamic characteristics of USVs in the marine environment, and it is difficult to apply it in actual scenarios. The authors of [28] draw on the idea of the velocity obstacle method and integrate the characteristics of the USV dynamics model, the encountering vessel motion model, COLREGS, etc, construct a USV local trajectory planner to generate real-time trajectories that meet the physical motion characteristics of USV for the USV control system This method does not consider the minimum resource cost between the collision avoidance strategy and the return original path.
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