access icon openaccess Vision-based map building and path planning method in unmanned air/ground vehicle cooperative systems

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 11/10/2019, Accepted 19/11/2019, Published 13/01/2020

To reduce the casualties and improve the efficiency of robot, unmanned air/ground vehicle (UAV/UGV) cooperative systems are proposed. In this study, mathematical algorithms are applied in a typical-rescue scenario. As a ‘flying eye’, the UAV provided the global information by vision sensor. Then, the images were processed with SURF algorithm and image binarisation to model the environment. Based on the UAV's information, the optimised A* algorithm was proposed. Finally, a feasible path was designed for UGV to rescue. Experiments are performed to evaluate the performances of the proposed method. Results show that SURF algorithm and image binarisation can realise the accuracy and robustness of map building. The optimised A* algorithm can provide a real-time and feasible path.

Inspec keywords: image sensors; cooperative systems; robot vision; path planning; mathematical programming; multi-robot systems; mobile robots; autonomous aerial vehicles

Other keywords: typical-rescue scenario; mathematical algorithms; path planning method; image binarisation; unmanned air-ground vehicle cooperative systems; vision sensor; vision-based map building; SURF algorithm; global information; flying eye; UAV's information

Subjects: Optimisation techniques; Mobile robots; Image sensors; Optimisation techniques; Optical, image and video signal processing; Aerospace control; Spatial variables control; Computer vision and image processing techniques

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