Feasibility study of a constrained Dijkstra approach for optimal path planning of an unmanned surface vehicle in a dynamic maritime environment

Abstract

Optimal path planning is an important part of mission management hierarchy in a modern unmanned surface vehicle (USV) guidance, navigation and control frame work. USVs operate in a complex dynamic marine environment comprising of moving obstacles and sea surface currents. These characterising variables of configuration space change spatially as well as temporally. The current work investigates a well-known search technique, the Dijkstra algorithm, to resolve the problem of motion planning for a USV moving in a maritime environment. The current study extends the implementation of Dijkstra algorithm in a space cluttered with static and moving obstacles. In addition, downstream and upstream effects of sea surface currents of different intensities on optimal path planning are studied. The performance is verified in simulations with total path length and elapsed computational time considered as parameters to determine the effectiveness of the adopted approach. The results showed that the approach is effective for global path planning of USVs.

Novel Implementation of Multiple Automated Ground Vehicles Traffic Real Time Control Algorithm for Warehouse Operations: Djikstra Approach

“…A brief explanation about these algorithms and the improvements were discussed below. (Singh et al, 2018) This algorithm is based on a greedy algorithm to find the shortest path between two points. This Dijkstra algorithm can only apply on the maps which are modelled using graph theory.…”

Self-Adaptive Dynamic Obstacle Avoidance and Path Planning for USV Under Complex Maritime Environment

“…The path planning algorithm focuses on designing an obstacle avoidance path according to known obstacles layout in the environment so as to reach the goal with the best efficiency [1]- [4]. Algorithms of A* [5] and Dijkstra [6] are classic methods for solving optimization problem of static path planning. Based on maritime obstacle avoidance rules, Kuwata et al [7] established geometric areas to divide obstacle avoidance zones and carried out the global obstacle avoidance planning of USV with the improved A* algorithm; Haiqing et al [8] combined the A* algorithm with the potential field method to formulate a dual-layer global planning algorithm, accordingly an optimized path advantaged in both the effective obstacle avoidance and short voyages was obtained; however, as for irregular obstacles, boundary information of obstacles is often effectively extracted with a grid method model, so a high-quality environmental model can be obtained and path planning can be realized based on interval geometric association [9].…”

“…From equation (6) we know, the value of the heuristic function depends on the reciprocal of current Euclidean distance between the USV and the feasible grids. The larger value is corresponding to the smaller probability for the grid to be selected as the local target.…”

3D path planner of an autonomous underwater vehicle to track an emitter using frequency and azimuth–elevation angle measurements

“…There exist many papers on path planning and control of various robots [10–14]. Many papers exist on tracking an emitter utilising an autonomous vehicle [15–18].…”