Comparative Study of Autonomous Path Planning Methods for Mobile Robot

Currently, robots are used to carry out dangerous tasks such as bomb detonations, spray painting, disaster management and so on. To ensure sufficient robot navigation, various path-planning methods are available in literature. These methods enable robots to create collision-free path in their working environments. Such environments can be either static (laboratory) or dynamic (realistic). The available path planning methods differ with respect to latency, applicability, computational load, power consumption rates and reliability. The ever-increasing applications of the mobile robots require computable and efficient methods. However, most path planning methods are theoretical, not always reliable and require huge computational resources, hence are not suitable for all real time applications. This paper is aimed at studying and comparing some of the available and important path planning methods for autonomous mobile robots in terms of characteristics of path planning methods, such as graph-based methods, sample-based methods and potential field methods. The paper compares characteristics of the path planning methods on the uniform performance index, by designing a comparison criterion. The performance of these methods will be studied based on the designed framework, including reliability, computational requirements, and power consumption rates. Recommendations towards a feasible solution with respect to the robot-working environment and the available resources will be provided.