Research on Real-Time Obstacle Avoidance Planning for an Unmanned Surface Vessel based on the Grid Cell Mechanism

Abstract

<jats:p>Obstacle avoidance navigation for an unmanned surface vessel is a research focus for ship autonomy in which the real-time requirement in practical application is very serious, and always necessitates a complicated structure model to guarantee real-time performance. This paper proposes the grid cell activation model to reduce the complexity of modelling and to simplify an obstacle avoidance algorithm. Combined with the goal-oriented probability model to design a dynamic positive-loss-rate expectation evaluation function, it produces the proper strategy for obstacle avoidance. Case studies on multi-obstacle layouts and special circumstances are conducted and presented. The results indicate that the grid cell obstacle avoidance algorithm can effectively implement obstacle avoidance planning and ensure real-time requirements. A comparison with the potential field algorithm is performed, which shows good results and verifies the feasibility of the algorithm.</jats:p>

Prescribed performance LOS guidance-based dynamic surface path following control of surface vessel with position and heading errors constraint

“…Ship motion control has received widespread attention to meet the needs of different tasks, realise the intelligence and automation of ships, and ensure the safety and economy of ships. The research on ships in recent years includes path planning (Lyu and Yin, 2019), collision avoidance (Li and Zheng, 2020; Xu et al, 2020) and track control. Track control is divided into trajectory tracking and path following.…”