Safe Avoidance Path Detection Using Multi Sensor Integration for Small Unmanned Aerial Vehicle
| Autor: | Ari Legowo, Muhammad Faiz Bin Ramli, Syariful Syafiq Shamsudin |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
020301 aerospace & aeronautics
0209 industrial biotechnology Computer science business.industry Feature extraction Perspective (graphical) Detector 02 engineering and technology 020901 industrial engineering & automation Lidar 0203 mechanical engineering Robustness (computer science) Obstacle Path (graph theory) Computer vision Artificial intelligence business Queue |
| Zdroj: | 2018 5th IEEE International Workshop on Metrology for AeroSpace (MetroAeroSpace). |
| DOI: | 10.1109/metroaerospace.2018.8453521 |
| Popis: | Achieving a robust obstacle detection system that can provide a safe avoidance path system for small UAV is very challenging. Due to size and weight constraints, very limited detection sensors can be equipped in the system. Prior works focused on a single sensing device which is either camera or range sensors based. However, these sensors have their own advantages and disadvantages in detecting the appearance of the obstacles. In this paper, a combination of both sensors based is proposed for a small UAV obstacle detection system. A small Lidar sensor is used as the initial detector of obstacle and queue for image capturing by the camera. Next, SURF algorithm is applied to find the obstacle regions and free space regions. This is done through the principal of object size changes and distance relationship in an image perspective. The proposed method was evaluated by conducting experiments in a real complex environment which consist of a textured and textureless obstacle. In the experiment conducted, we successfully detect and create a safe avoidance path for both situations. The textured situation gives a high success rate while textureless situation produces acceptable success rate until 60cm distance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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