Abstract
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.
Highlights
An Unmanned Aerial Vehicle (UAV) as the name implies, it is an aircraft without a pilot onboard or attached to it
Obstacle detection and avoidance is desirable for UAVs especially lightweight micro aerial vehicles and is challenging problem since it has payload constraints, only limited sensor can be attached the vehicle
We combine Speeded Up Robust Features (SURF) algorithm with Harris corner detector to determine the approximate size of the obstacles
Summary
An Unmanned Aerial Vehicle (UAV) as the name implies, it is an aircraft without a pilot onboard or attached to it It can fly autonomously by pre-programmed the UAV’s system or controlled manually by the pilot on the ground. Commercial UAVs are already equiped with single camera (monocular vision) onboard and can be pre-programed to use features based detection techniques. Plus, considering the size, weight, power consumption and capability to extract useful information, camera is the most competitive tool for UAV [4].this dissertation mainly aims at developing a real-time obstacles detection and avoidance system based on multi-sensor integration (combination of optical and laser sensors) to achieve autonomous operation for UAVs. Plus, the aims is to estimates or approximates the size congfiguration of the obstacles for safe avoidance purposes
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