Efficient Interpolated Path Planning of Mobile Robots based on Occupancy Grid Maps

This paper focuses on interpolation-based path planning algorithms for mobile robot that use the occupancy grid map of the environment. Such an algorithm produces the path close to optimal solution in continuous search space, but has computational burden. We discuss on using heuristics to improve efficiency of the E* algorithm, as the interpolation-based path planning algorithm, with a trade-off of generating less optimal paths. We compare obtained paths with the almost optimal solution in continuous search space and also with the path obtained by the D* algorithm, which is a representative of the classical graph search algorithms applied on the occupancy grid map. All used algorithms are verified both by simulation and experimentally on a Pioneer 3DX mobile robot equipped with a laser range finder.