Comparing RRT and RRT* for Path Planning for UAV in the 3D Urban Occupancy Model
Zihan Chen, Di Kang, Yapeng Wang, Xu Yang, Sio‐Kei Im · 2023
This paper explores the use of MATLAB's UAV Toolbox to simulate the flight path of Unmanned Aerial Vehicles (UAVs) in a 3D city model using the Rapidly exploring Random Tree (RRT) and RRT* algorithms. We employed both quantitative and qualitative methods to evaluate the performance of these algorithms. The study begins with the implementation of the algorithms in MATLAB, followed by the creation of a 3D city model. The UAV's flight path is then simulated within this model, taking into account various factors such as obstacles and optimal paths. The reproducibility of simulations in MATLAB is crucial for testing and validating the results. It allows for the fine-tuning of the algorithms and the model, leading to more accurate and reliable results. Lastly, MATLAB's easy integration with other software and hardware makes it a suitable platform for developing and testing real-world applications. This study demonstrates the potential of MATLAB in enhancing the safety and efficiency of UAV operations in urban areas, providing valuable insights for future research and development in the field of UAV navigation and control.