Metaheuristic global path planning algorithm for mobile robots

Abstract

Abstract:A new metaheuristic method applied to the global path planning for mobile robots in dynamic environments is presented. This algorithm, named the Quad Harmony Search method, consists of dividing the robot"s environment into free regions by applying the Quad-tree algorithm and utilizing this information to accelerate the next phase which implements the Harmony Search optimization method to provide the optimal route. The presented results have displayed that this method gives best results when compared to other metaheuristic techniques and is therefore applicable to the global path planning problem.

Uncertain estimation-based motion-planning algorithms for mobile robots

“…Motion-planning algorithms can be divided into two parts. If all the data for the robot's environment are known and available at the start, then global motion-planning algorithms can be used to generate a collision-free path [1], [2]. However, if the robot can only use local sensor-based information about its surrounding dnese and dynamic environment, then reactive motion-planning algorithms can provide an acceptable solution for generating the robot's path and velocity [3], [4].…”

Novel Motion Planning Method for Mobile Robots Using Velocity Obstacle

“…If every information is given as a priori information, then offline global motion planning methods (e.g. : Rapidly-exploring random tree (RRT) [4]- [5], Hybrid A* [6], Metaheuristic Global Path planning [7]) can ensure a suitable solution. If there is only local information about the environment, online reactive motion planning algorithms should be applied.…”