An image-based path planning algorithm using a UAV equipped with stereo vision

İz, Selim Ahmet and Ünel, Mustafa (2022) An image-based path planning algorithm using a UAV equipped with stereo vision. In: 48th Annual Conference of the Industrial Electronics Society (IECON 2022), Brussels (Accepted)

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Abstract

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.
Item Type: Papers in Conference Proceedings
Subjects: T Technology > TJ Mechanical engineering and machinery > TJ163.12 Mechatronics
T Technology > TJ Mechanical engineering and machinery > TJ210.2-211.47 Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General)
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Mechatronics
Faculty of Engineering and Natural Sciences
Depositing User: Mustafa Ünel
Date Deposited: 08 Oct 2022 14:33
Last Modified: 08 Oct 2022 14:33
URI: https://research.sabanciuniv.edu/id/eprint/44548

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