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In recent times, there is an impressive progress in the field of automation and robotics. Google driverless car or intelligent Unmanned Air Vehicle (UAV) is the latest in the research works aiming for a high degree of autonomy. In this research field of automation and robotics, there is a mandatory requirement of continuously improving path planning algorithms. Path planners aim in finding an optimal and collision-free path in the work environment. The purpose of path planning is to find a kinematical optimal path with the least time complexity as well as model the environment completely. In this paper, we discuss the most successful robot path planning algorithms which have been developed in recent years from different field of science, making it a multidisciplinary approach and concentrate on universally applicable algorithms which can be implemented in aerial robots, ground robots and underwater robots. The algorithms are analysed from an optimality and completeness area perspective. In our study, we have included the Dynamic Programming Planning approach also which none of the review papers have covered. |
