Object detection technique for small unmanned aerial vehicle
Obstacle detection and avoidance is desirable for UAVs especially lightweight micro aerial vehicles and is challenging problem since it has payload constraints, therefore only limited sensor can be attached the vehicle. Usually the sensors incorporated in the system is either type vision based (mono...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English English English |
| Published: |
IOP
2017
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/58901/1/ICOM_2017_Ari%20Legowo.pdf http://irep.iium.edu.my/58901/7/58901_Object%20Detection%20Technique_tentative.pdf http://irep.iium.edu.my/58901/18/58901_Object%20detection%20technique.pdf http://irep.iium.edu.my/58901/24/58901%20Object%20detection%20technique%20for%20small%20unmanned%20aerial%20vehicle%20SCOPUS.pdf http://irep.iium.edu.my/58901/ http://www.iium.edu.my/icom/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Obstacle detection and avoidance is desirable for UAVs especially lightweight micro aerial vehicles and is challenging problem since it has payload constraints, therefore only limited sensor can be attached the vehicle. Usually the sensors incorporated in the system is either type vision based (monocular or stereo camera) or Laser based. However, each of the sensor has its own advantage and disadvantage, thus we built the obstacle detection and avoidance system based multi sensor (monocular sensor and LIDAR) integration. On top of that, we also combine SURF algorithm with Harris corner detector to determine the approximate size of the obstacles. In the initial experiment conducted, we successfully detect and determine the size of the obstacles with 3 different obstacles. The differences of length between real obstacles and our algorithm are considered acceptable which is about -0.4 to 3.6. |
|---|