Exploring RRT and BiRRT Algorithms: A Review and Simulation-Based Comparison for Fixed-Wing UAV Path Planning

Gilang Nugraha Putu Pratama; Oktaf Agni Dhewa; Mentari Putri Jati; Indra Hidayatulloh; Teddy Surya Gunawan; Syaiful Ardy Gunawan

doi:10.12928/biste.v8i2.14511

Authors

Gilang Nugraha Putu Pratama Universitas Negeri Yogyakarta
Oktaf Agni Dhewa Universitas Negeri Yogyakarta
Mentari Putri Jati National Taipei University of Technology
Indra Hidayatulloh Glasgow Caledonian University
Teddy Surya Gunawan International Islamic University Malaysia
Syaiful Ardy Gunawan Seiko Epson Corporation

DOI:

https://doi.org/10.12928/biste.v8i2.14511

Keywords:

RRT, BiRRT, Path Planning, Fixed-Wing, UAV

Abstract

Path planning plays a vital role in ensuring the safe and efficient navigation of fixed-wing unmanned aerial vehicles (UAVs), particularly in cluttered and complex environments. The increasing demand for autonomous UAV operations highlights the need for reliable algorithms capable of generating optimal and collision-free trajectories. This study addresses the challenge by reviewing recent uses of the Rapidly-exploring Random Tree (RRT) algorithm in various robotic platforms and navigation tasks. The research contribution of this paper is a comparative analysis of RRT and BiRRT for fixed-wing UAV path planning, quantifying trade-offs between path length, computation time, and obstacle clearance using a real-world 2D urban map. This addresses a gap in the literature, as few studies have directly compared these algorithms specifically for fixed-wing UAV surveillance missions. The methods involve implementing both RRT and BiRRT in a simulated environment where each algorithm is evaluated over 100 runs to measure performance metrics such as path length, computation time, and obstacle clearance. A realistic urban map is used to test the algorithms under consistent starting and goal positions. The results show that both RRT and BiRRT achieve a 100% success rate in finding collision-free paths. BiRRT consistently generates shorter paths and requires less computation time, making it more suitable for time-sensitive missions. However, RRT produces safer trajectories with greater average clearance from obstacles, which is advantageous in environments with high collision risk. The findings demonstrate a clear trade-off between safety and efficiency. In conclusion, BiRRT is recommended for missions where speed and efficiency are prioritized, while RRT is better suited for operations emphasizing safety and obstacle avoidance.

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