Performance Improvement of RRT* Family Algorithms by Limiting Sampling Range in Circular and Spherical Obstacle Environments (vol 50, pg 809, 2022)

The development of unmanned robots and UAVs has increased the need for path planning methods such as RRT* algorithm. It mostly works well in various environments and is utilized in many fields. A lot of research has been conducted to obtain a better path in terms of efficiency through various modifications to the RRT* algorithm, and the performance of the algorithm is continuously improved thanks to these efforts. In this study, a method using the limitation of sampling range is proposed as an extension of these efforts. Based on the idea that a path passing close to obstacles is similar to the optimal path in obstacle environments, nodes are produced around the obstacle. Also, rewiring algorithm is modified to quickly obtain the path. The performance of the proposed algorithm is validated by comparative analysis of the previous basic algorithm and the generated path is tracked by a UAV's kinematic model for further verification.