Path Planning of an Unmanned Surface Vessel Based on the Improved A-Star and Dynamic Window Method

Abstract

In order to ensure the safe navigation of USVs (unmanned surface vessels) and real-time collision avoidance, this study conducts global and local path planning for USVs in a variable dynamic environment, while local path planning is proposed under the consideration of USV motion characteristics and COLREGs (International Convention on Regulations for Collision Avoidance at Sea) requirements. First, the basis of collision avoidance decisions based on the dynamic window method is introduced. Second, the knowledge of local collision avoidance theory is used to study the local path planning of USV, and finally, simulation experiments are carried out in different situations and environments containing unknown obstacles. The local path planning experiments with unknown obstacles can prove that the local path planning algorithm proposed in this study has good results and can ensure that the USV makes collision avoidance decisions based on COLREGs when it meets with a ship.

Global Path Planning for Autonomous Ship Navigation Considering the Practical Characteristics of the Port of Ulsan

“…The authors of another study considered motion characteristics and ENCs of areas such as those near the port sea area using a route planning algorithm [24]. The A* algorithm and dynamic window methods are instrumental in complex port terrains, focusing on comprehensive path planning and collision avoidance [25]. Further studies have integrated the improved Artificial Potential Field (APF) algorithm in hybrid path planning methods [26].…”

Optimizing Mobile Robot Navigation Based on A-Star Algorithm for Obstacle Avoidance in Smart Agriculture

“…The end objective is to support the implementation of precision agricultural technologies and promote sustainable food production. These efforts aim to minimize the choppiness in generated paths, thereby ensuring that autonomous vehicles and robotic systems can navigate agricultural environments more efficiently [26][27][28][29].…”

Distributed Swarm Trajectory Planning for Autonomous Surface Vehicles in Complex Sea Environments

“…The trajectory-planning problem of an ASV has been widely studied in the literature [14][15][16][17][18][19][20][21]. Specifically, in [14], a temporal-logic-based ASV path-planning method is employed, which enables the ASV to pass through heavy harbor traffic to an intended destination in a collision-free manner.…”

“…Furthermore, in [20], the particle swarm optimization algorithm together with the visibility graph is applied to the ASV path-planning problem among complex shorelines and spatiotemporal environmental forces. Recently, in [21], a hybrid artificial potential field method is proposed for an ASV cruising in a dynamic riverine environment. However, it is worth mentioning that the works [14][15][16][17][18][19][20][21] are dedicated to the path planning of a single ASV.…”