Abstract
We consider the problem of a drone (quadcopter) that needs to detect and avoid an obstacle when autonomously flying in an unknown maze of walls and obstacles. The detector performs two tasks: • Detect that the drone is close to colliding with an object if the drone continues flying in its current direction. • Once a close object has been detected the drone will start turning and the detector should signal when to stop this turn as an obstacle-free direction has been detected. This camera-based detector must be of low complexity as it is intended to be used by low-weight/battery drones whose controllers (such as the Raspberry PI0) can not support heavy computations. This ability is a fundamental problem in the area of drones (even in general robotics). In this work, we propose such a camera-based detector whose complexity improves upon previously proposed techniques. In previous works, key points are extracted, and based on their relative position-disparity in two consecutive frames, either true distances or the shape of a close object are computed. Rather than compute distances or the shape of a close object we use the horizontal disparity (roll angle 0) just to compute the probability that there is a close object in front of the drone. This reduces the overall complexity significantly, yet our experiments in flight simulation mode show a high detection ratio.
Original language | English |
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Title of host publication | Europe ISR 2023 - International Symposium on Robotics, Proceedings |
Publisher | VDE Verlag GmbH |
Pages | 189-196 |
Number of pages | 8 |
ISBN (Electronic) | 9783800761418 |
State | Published - 2023 |
Event | 56th International Symposium on Robotics, ISR Europe 2023 - Stuttgart, Germany Duration: 26 Sep 2023 → 27 Sep 2023 |
Publication series
Name | Europe ISR 2023 - International Symposium on Robotics, Proceedings |
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Conference
Conference | 56th International Symposium on Robotics, ISR Europe 2023 |
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Country/Territory | Germany |
City | Stuttgart |
Period | 26/09/23 → 27/09/23 |
Bibliographical note
Publisher Copyright:© VDE VERLAG GMBH Berlin Offenbach.
Keywords
- Kalman filter
- Key points detectors
- Monocular vision
- Obstacle Detection
- Small drones
ASJC Scopus subject areas
- Artificial Intelligence
- Human-Computer Interaction
- Software