| Research Title |
Obstacle Detection and Avoidance based on 3D Stereoscopic Technique for Autonomous Drone |
| Date of Distribution |
25 November 2021 |
| Conference |
| Title of the Conference |
2021 13th International Conference on Information Technology and Electrical Engineering (ICITEE) |
| Organiser |
IEEE Computational Intelligence Society Thailand Chapter |
| Conference Place |
ONLINE VIRTUAL CONFERENCE |
| Province/State |
Chiang Mai, Thailand |
| Conference Date |
15 November 2021 |
| To |
16 November 2021 |
| Proceeding Paper |
| Volume |
2564 |
| Issue |
13th |
| Page |
86-91 |
| Editors/edition/publisher |
Thanawut Nabandit; Saiyan Saiyod; Woottichai Nonsakhoo; Piyanat Sirisawat |
| Abstract |
Autonomous drones are drones that can fly on their own without the need for human supervision. Once the drone is assigned a flight mission, it will automatically fly to its destination. The ability to quickly maneuver obstacles is essential to complete the task assigned to it. Obstacle analysis processes need to be efficient and require fewer computing resources due to the hardware and power constraints of drones. This work presents a simple but effective way to detect obstacles using a 3D Stereoscopic camera and a less complicated image processing method, which can run on a small single-board computer. On-site flight tests show that the proposed method can be used efficiently. It can detect obstacles at a distance of 2 meters, 5 frames per second, 79.55% of detection accuracy, and maneuver effectively. |
| Author |
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| Peer Review Status |
มีผู้ประเมินอิสระ |
| Level of Conference |
นานาชาติ |
| Type of Proceeding |
Full paper |
| Type of Presentation |
Oral |
| Part of thesis |
true |
| Presentation awarding |
false |
| Attach file |
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| Citation |
0
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Publication
Journal Publication
ไทย