Path planning based on Constrained Delaunay Triangulation

This paper proposes a path planning algorithm for determining an optimal path with respect to the costs of a dual graph on the Constrained Delaunay Triangulation (CDT) of an environment. The advantages of using triangles for environment expression are: less data storage required, available mature triangulation methods and consistent with a potential motion planning framework. First we represent the polygon environment as a planar straight line graph (PSLG) described as a collection of vertices and segments, and then we adopt the CDT to partition the environment into triangles. Then on this CDT of the environment, a dual graph is constructed following the target attractive principle in order to avoid the nonoptimal paths caused by the different geometric size of the triangles. Correspondingly, a path planning algorithm via A* search algorithm finds an optimal path on the real-time building dual graph. In addition, completeness and optimization analysis of the algorithm is given. The simulation results demonstrate the effectiveness and optimization of the algorithm.