A new local path planning approach by synthesis of PRM and RRT* algorithms for an autonomous mobile robot

Many research efforts have been and continue to be carried out to make human life easier through the use of new technologies. The ability to shift labor to non-humans and reduce the workforce demonstrates the scope of innovation. In this investigation, a new approach is proposed to address several shortcomings of the PRM and RRT algorithms used for path planning in mobile robots. The proposed approach differs by building markers around it, avoiding dynamic obstacles and providing a shorter path. Simulation studies of the PRM and RRT* algorithms, along with the Circular Nodes (CN) approach, were conducted in real and virtual environments. Meanwhile, experimental studies for the CN approach were carried out in a real environment, with obstacles. When compared to other methods, the proposed approach has demonstrated an increase in node efficiency by up to five times. Moreover, implementing node points that are approximately 10% of those used in the PRM and RRT* algorithms has resulted in a shorter path. The reduction in the number of nodes and path length leads to a reduction in energy consumption and processing power.