Development of a Sampling-Based UAV Path Planner for Collision-Free Navigation

Unmanned aerial vehicles (UAVs) have become immensely popular in various applications, from surveillance, monitoring to package delivery, search, and rescue missions. Efficient path planning is a crucial aspect of UAV operations to ensure safe and optimal navigation in complex environments. Given its efficient detection of ideal paths, the A* algorithm has drawn considerable interest in the world of path planning. This paper presents an extensive investigation of the A* algorithm and its application in UAV path planning. The objective of this investigation is to analyze the performance of A* in terms of path optimality and versatility across various test cases. The paper provides a comprehensive overview of the algorithm, including its underlying principles and heuristic search strategy. Through the means of this, we have tested the proposed algorithms on various test cases and obtained collision-free traversal.