Path Planning and Collision Avoidance in Unknown Environments for USVs Based on an Improved D* Lite

Abstract

Path planning and collision avoidance during autonomous navigation in unknown environments is a crucial issue for unmanned surface vehicles (USVs). This paper improves the traditional D* Lite algorithm and achieves multi-goal path planning and collision avoidance for USVs in unknown and complex environments. By expanding the adjacent search range and setting a safe distance for USVs, we solve the issue of limited steering maneuverability in USVs with fewer DOF during autonomous navigation. We propose an approach to optimize the planned path during navigation by comparing the estimated distance with the actual distance between the current waypoint and the goal waypoint. A minimum binary heap is used to optimize the priority queue of the D* Lite and significantly reduce the path search time. Simulation results show that the improved D * Lite can significantly reduce the path planning time, optimize the planned path and solve the issue of limited steering maneuverability in USVs. We apply the algorithm to a real USV for further tests. Experimental results show that the USV can plan an optimized path while avoiding both static and dynamic obstacles in complex environments with a safe distance during autonomous navigation.

Path Planning For Unmanned Surface Vehicles Based On Modified Artificial Fish Swarm Algorithm With Local Optimizer

“…In prey behavior, the food concentration of all the potential positions in P is calculated and then the best position X p i,best is selected to be the next step, as shown in ( 8) and (9). Te directional operator frstly guarantees the AF can fnd the best position with one cycle of calculation, which signifcantly reduces the computing time.…”

“…Recently, there has been a growing appeal for path planning algorithms with the vigorous development of artifcial intelligence [5,6]. Developing path planning algorithms with high computing efciency, robustness, and high-quality solutions is an attractive topic in the current studies [7][8][9]. Qin et al [10] proposed a rapid USV path planning algorithm to decrease the computational complexity.…”

Improved Dynamic Window Approach for Unmanned Surface Vehicles’ Local Path Planning Considering the Impact of Environmental Factors

“…Global path planning is realized mainly with the waypoint method, which applies to cases where there are only static obstacles and all environmental information is available in advance, that is, one point is left at each interval and then each adjacent waypoint is connected with a straight line to generate the shortest path without the time and the other parameters. The A* method [ 4 ] and D* Lite method [ 5 ] are classic global path planning methods, usually with low resolution, and have been applied to autonomous underwater vehicles (AUVs) in early years [ 6 , 7 , 8 ]. However, AUVs and USVs have differences in functional areas, environmental conditions, running speed, and load capacity.…”

Three-Dimensional Obstacle Avoidance Strategy for Fixed-Wing UAVs Based on Quaternion Method

“…These applications commonly require the UAV to autonomously track predefined waypoints or prescribed trajectories. In addition, the autonomous detection of potential threats and an online obstacle avoidance algorithm are necessary for UAVs to ensure adequate security [1]. Accordingly, the control problem of UAVs is a multi-objective issue, which indicates that it is extremely important to introduce an integrated approach, taking into account global navigation as well as the local potential obstacle avoidance simultaneously.…”