An Effective Implementation and Comparative Analysis of Mobile Robot Path Planning Algorithms

Among the most pressing and intricate challenges in control and computer engineering today is the navigation of autonomous mobile robots. People are now more motivated than ever to use innovative methods, thanks to the development of cutting-edge computational engineering technology. In order to address complicated engineering challenges in the real world, researchers have mostly looked to natural occurrences and their methods for inspiration. In challenging and dense environments, path planning is the best way of defining a safe route in which a mobile robot can navigate to achieve a certain goal from another location. Mobile robots thus require smart and efficient route planning algorithms for proper navigation and self-execution capabilities. In this study, four well-known algorithms for route planning were investigated: Hybrid DA+CS algorithm: The proposed methods DA, CS and PSO using a non-holonomic mobile robot. To test these methods, a test environment has been created with static impediments which will remain constant throughout the experiment. This is because it is where the intended route of the mobile robot is followed and where the availability of the map acquired for path planning algorithms allows assessing and testing them. A comparative study of the following algorithms has been carried out in an effort to understand the trade off between them based on the conventional performance indicators being used.