Wind direction and speed estimation for quadrotor based gas tracking robot

Eu, Kok Seng * and Chia, Wei Zheng and Yap, Kian Meng * (2017) Wind direction and speed estimation for quadrotor based gas tracking robot. In: Mobile and wireless technologies. Lecture Notes in Electrical Engineering (425). Springer Science+Business Media, Singapore, pp. 645-652. ISBN 978-981-10-5280-4

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In gas extraction sites, the incidents of gas leaking poses a damage to workers on site. The protection for the workers is essential. However, due to the colorless and odorless nature of natural gas, it is difficult for humans to identify leaks. This paper proposes a quadrotor based gas tracking robot to be used in hazardous gas localization areas, and specifically, to detect methane leak from gas extraction sites. For the quadrotor to fulfill this purpose, it requires the ability to detect wind direction and speed, an endowment that commercial quadrotors lack. The need to detect wind direction and speed stems from the fact that gas plumes travel downwind, but the quadrotor needs to find the source of the leak, and hence, must determine the upwind direction to locate the source. In order to equip the quadrotor with the above skills, a wind direction and speed estimation algorithm based on Euler angles-velocity vectors has been proposed. For comparison purposes, we compared the proposed method with a generic ultrasonic wind sensor. We concluded that the proposed method achieves an error percentage as low as 10.73% for wind speed, and 9.09% for wind direction estimation. Thus, the algorithm is a significant addition to the quadrotors’ capabilities, enabling the quadrotor to trace upwards, against the traversal of the gas plume, and carry out accurate calculations

Item Type: Book Section
Subjects: T Technology > T Technology (General)
Divisions: Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computing and Information Systems
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 13 Jul 2017 08:59
Last Modified: 02 May 2019 08:06

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