Voronoi-Visibility Roadmap-based Path Planning Algorithm for Unmanned Surface Vehicles

Abstract

In this paper, a novel Voronoi-Visibility (VV) path planning algorithm, which integrates the merits of a Voronoi diagram and a Visibility graph, is proposed for solving the Unmanned Surface Vehicle (USV) path planning problem. The VM (Voronoi shortest path refined by Minimising the number of waypoints) algorithm was applied for performance comparison. The VV and VM algorithms were compared in ten Singapore Strait missions and five Croatian missions. To test the computational time, a high-resolution, large spatial dataset was used. It was demonstrated that the proposed algorithm not only improved the quality of the Voronoi shortest path but also maintained the computational efficiency of the Voronoi diagram in dealing with different geographical scenarios, while also keeping the USV at a configurable clearance distance c from coastlines. Quantitative results were generated by comparing the Voronoi, VM and VV algorithms in 2,000 randomly generated missions using the Singapore dataset.

Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning

“…In [19], autonomous exploration and mapping strategy was developed for a heterogeneous multi-robot systems including both quadrotors and wheeled mobile robots. Even though exploring a static environment using a team of robots has been investigated extensively [20], [21], dealing with unexpected obstacles, such as human movements and dynamic environments, remains an open question.…”

The review unmanned surface vehicle path planning: Based on multi-modality constraint

“…A. et al, 2017;Kim, J. et al, 2011;Huajun, L. et al, 2006;Huai Yang. 2016;Chao C., et al, 2014;Candeloro M. et al, 2017;Niu et al, 2019;Yang, J. M. et al, 2015). One of the most widely used ways of environment modeling in Route Planning is Grid Map (Raster Map).…”

“…Figure 6 shows the Visibility Graph, Figure 7 shows the Voronoi Diagram, Figure 8 shows the grid map. Figure 6 Visibility Graph (Chao C., et al, 2014) Figure 7 Voronoi roadmap of polygon obstacles (Niu, H., et al, 2019) Figure 8 the Grid Map (Song, R. et al, 2019) Generally, search-path time, search-path completeness and search-path optimality are the main factors for performance of search-path algorithm (Latip, N. B. A. et al, 2017).…”

A New Challenge: Path Planning for Autonomous Truck of Open-Pit Mines in The Last Transport Section

“…For the heuristic algorithm, the map cost value directly affects the accuracy of the estimation function, thus affecting the quality of the final path. Voronoi diagram is a geometry-based route planning method for robot path planning [36,37], which divides the space into several regional units according to the nearest neighbor attributes of the elements in the site collection. Dolgov [30], the inventor of the Hybrid A* algorithm, used the generalized Voronoi diagram to generate the planning map, which made the planning path can pass through the narrow area and without collision.…”