Effects of heuristics in path planning for mobile robots in uncertain and dynamic environments

In this work, several heuristics are proposed to assess their effects in path planning for mobile robots in uncertain and dynamic environments. Path planning for mobile robots is a widely used technique where an optimal collision-free path is searched through an environment. It is one of the most important primitives in robotics and is considered to be a hard problem. Since environments may contain static as well as dynamic obstacles, the optimal path must be collision-free. The situation becomes complicated for mobile robots when an environment consists of dynamic obstacles with random velocities and arbitrary directions. Though there have been a lot of research in static environments, concentration given on uncertain and dynamic environments is a few. Our goal is to find a path in such uncertain and dynamic environments considering simulation time and travel-distance. In order to analyze the robustness of our proposed heuristics, we plugged each of these heuristics in several search algorithms. We also compared the performances of these algorithms. Finally, this paper analyzes the effects of the proposed heuristics in path planning in uncertain and dynamic environments which are usual real-word scenarios for mobile robots.