An Evaluation of Hybrid RRT* with Anytime RRT* Algorithm for Wheeled Mobile Robot

In robotics applications, real-time path planning is essential for allowing robots to travel effectively and independently in changing situations. While they offer the best results, traditional path planning algorithms cannot adjust to changing circumstances. This study suggests a hybrid strategy to accomplish effective and anytime-capable path planning for a wheeled mobile robot (WMR) by combining the advantages of the RRT* and Anytime RRT* algorithms. The anytime behaviour of Anytime RRT* is integrated into the RRT* algorithm via the hybrid algorithm known as Hybrid RRT* with Anytime RRT*. This enables the robot to repeatedly improve solution quality and quickly construct an initial viable path using RRT*. It may then adjust this path over time in response to changes in the environment. Real-time tests on a WMR platform and simulations are used to assess the algorithm’s performance. Creating a simulation environment with different step sizes and iterations is part of the experimental setup. The algorithm’s success is evaluated using performance indicators such as cleaning time, cleaning efficiency, collisions, and near-collisions. The comparison of the outcomes with the conventional RRT* and Anytime RRT* implementations sheds light on the flexibility and efficiency benefits of the hybrid method. Furthermore, the algorithm’s performance in dynamic situations is validated by the algorithm’s real-time implementation on the WMR. The study advances the area of real-time path planning by introducing a unique hybrid method that integrates the advantages of Anytime RRT* and RRT*. The results demonstrate the flexibility, effectiveness, and high quality of the solution provided by the algorithm.