Abstract
Unmanned aerial vehicles (UAVs) can be applied as an inspection method for infrastructures such as tunnels, bridges, etc. In particular, UAVs being capable of vertical takeoff and landing (VTOL) are suitable for photographing inspection sites using cameras, because it need not use a runway and can hover. Among such VTOL type UAVs, those having four rotors are called Quadrotors. When using a Quadrotor for infrastructure inspection, it needs to approach the inspection object in order to photograph the inspection site using the camera. However, due to the influence by wind, it is predicted that the Quadrotor will collide with the inspection object. When the airframe comes into contact with the inspection object, there are problems that the camera image, which is provided a camera mounted on the airframe, is distorted, and the airframe and the inspection objects are damaged. Thus, it is necessary for the inspection Quadrotor to avoid a contact with the inspection object. Therefore, the present research is a wall surface detection method using ultrasonic sensors, so as to realize collision avoidance between walls or piers and the camera mounted Quadrotor. In this paper, we report a wall surface detection method, wall surface detection experiments using the proposed ultrasonic sensors and their results.
Original language | English |
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Title of host publication | 2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1438-1443 |
Number of pages | 6 |
ISBN (Electronic) | 9781509067572 |
DOIs | |
Publication status | Published - Aug 23 2017 |
Event | 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 - Takamatsu, Japan Duration: Aug 6 2017 → Aug 9 2017 |
Other
Other | 14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 |
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Country/Territory | Japan |
City | Takamatsu |
Period | 8/6/17 → 8/9/17 |
Keywords
- Collision Avoidance
- Quadrotor
- Wall Surface Detection
ASJC Scopus subject areas
- Control and Optimization
- Instrumentation
- Artificial Intelligence
- Industrial and Manufacturing Engineering
- Mechanical Engineering