Traversal of Unmanned Autonomous Vehicles Through Arbitrarily Shaped Openings

In recent years, deploying unmanned aerial and ground vehicles has become increasingly prevalent across various domains, such as agriculture, defense, and filmmaking, owing to their versatility and efficiency. Despite their widespread use, these robots are still facing challenges in certain scenarios, particularly in navigating through arbitrarily shaped openings. This paper addresses the above challenge by proposing algorithms designed for opening detection and feasibility checks, ensuring safe passage through these complex environments. The core of this work revolves around the contour detection algorithm, developed using OpenCV, and the optimal rectangle extraction algorithm, which significantly enhances computational efficiency and is employed to fit an optimal rectangle within the detected contour. This step is crucial for ensuring the robot's safety by generating a feasible goal point for the point-tracking algorithm to follow. To validate the effectiveness of the proposed algorithms, a comprehensive experimental setup, including a ground robot equipped with various state estimation techniques, was established. Extensive testing and validation were conducted within this experimental framework, demonstrating the robustness and reliability of the algorithms in real-world scenarios. The successful implementation of these algorithms in hardware attests to this research's practical applicability and potential impact.