An Image-Based Path Planning Algorithm Using a UAV Equipped with Stereo Vision

• Published in: IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society pp. 1 - 6
• Main Authors: Iz, Selim Ahmet, Unel, Mustafa
• Format: Conference Proceeding
• Language: English
• Published: IEEE 17.10.2022
• Subjects: ArUco marker; Computer Vision; Heterogeneous Robot Collaboration; Heuristic algorithms; Mathematical models; Mobile Robotics; Path Planning; Probabilistic logic; Service robots; Stereo Depth Reconstruction; Surface reconstruction; Three-dimensional displays; Trajectory; V-REP
• ISSN: 2577-1647
• DOI: 10.1109/IECON49645.2022.9968613

This paper presents a novel image-based path planning algorithm that was developed using computer vision techniques, as well as its comparative analysis with well-known deterministic and probabilistic algorithms, namely A* and Probabilistic Road Map algorithm (PRM). The terrain depth has a significant impact on the calculated path safety. The craters and hills on the surface cannot be distinguished in a two-dimensional image. The proposed method uses a disparity map of the terrain that is generated by using a UAV. Several computer vision techniques, including edge, line and corner detection methods, as well as the stereo depth reconstruction technique, are applied to the captured images and the found disparity map is used to define candidate way-points of the trajectory. The initial and desired points are detected automatically using ArUco marker pose estimation and circle detection techniques. After presenting the mathematical model and vision techniques, the developed algorithm is compared with well-known algorithms on different virtual scenes created in the V-REP simulation program and a physical setup created in a laboratory environment. Results are promising and demonstrate effectiveness of the proposed algorithm.