Localization of Small-Size Unmanned Air Vehicles (UAVs) such as the Quadrotors in Global Position... more Localization of Small-Size Unmanned Air Vehicles (UAVs) such as the Quadrotors in Global Positioning System (GPS)-denied environment such as indoors has been done using various techniques. Most of the experiment indoors that requires localization of UAVs, used cameras or ul- trasonic sensors installed indoor or applied indoor environment modification such as patching (Infra Red) IR and visual markers. While these systems have high accuracy for the UAV localization, they are expensive and have less practicality in real situations. In this paper a system consisting of a stereo camera embedded on a quadrotor UAV (QUAV) for indoor localization was proposed. The optical flow data from the stereo camera then are fused with attitude and acceleration data from our sen- sors to get better estimation of the quadrotor location. The quadrotor altitude is estimated using Scale Invariant Feature Transform (SIFT) Feature Stereo Matching in addition to the one computed using optical flow. To avoid latency due to computational time, image processing and the quadrotor control are processed threads and core allocation. The performance of our QUAV altitude estimation is better compared to single-camera embedded QUAVs due to the stereo camera triangulation, where it leads to better estimation of the x-y position using optical flow when fused together.
Page 1. Journal of System Design and Dynamics Vol.4, No.2, 2010 Autonomous Hovering and Landing o... more Page 1. Journal of System Design and Dynamics Vol.4, No.2, 2010 Autonomous Hovering and Landing of a Quad-rotor Micro Aerial Vehicle by Means of on Ground Stereo Vision System ∗ Dwi PEBRIANTI ∗∗ , Farid KENDOUL ∗∗∗ , Syaril AZRAD ∗∗ , ...
This paper describes an object tracking system using an autonomous micro air vehicle (MAV) and de... more This paper describes an object tracking system using an autonomous micro air vehicle (MAV) and demonstrate its potential use for civilian purposes. The vision-based control system relies on a color and feature based vision algorithm for target detection and tracking, Kalman filters for relative pose estimation, and a nonlinear controller for MAV stabilization and guidance. The vision algorithm relies on information from a single onboard camera. An arbitrary target can be selected in real-time from the ground control station, thereby outperforming template and learning-based approaches. Experimental results obtained from outdoor flight tests, showed that the vision-control system enabled the MAV to track and hover above the target as long as the battery is available.
Localization of Small-Size Unmanned Air Vehicles (UAVs) such as the Quadrotors in Global Position... more Localization of Small-Size Unmanned Air Vehicles (UAVs) such as the Quadrotors in Global Positioning System (GPS)-denied environment such as indoors has been done using various techniques. Most of the experiment indoors that requires localization of UAVs, used cameras or ul- trasonic sensors installed indoor or applied indoor environment modification such as patching (Infra Red) IR and visual markers. While these systems have high accuracy for the UAV localization, they are expensive and have less practicality in real situations. In this paper a system consisting of a stereo camera embedded on a quadrotor UAV (QUAV) for indoor localization was proposed. The optical flow data from the stereo camera then are fused with attitude and acceleration data from our sen- sors to get better estimation of the quadrotor location. The quadrotor altitude is estimated using Scale Invariant Feature Transform (SIFT) Feature Stereo Matching in addition to the one computed using optical flow. To avoid latency due to computational time, image processing and the quadrotor control are processed threads and core allocation. The performance of our QUAV altitude estimation is better compared to single-camera embedded QUAVs due to the stereo camera triangulation, where it leads to better estimation of the x-y position using optical flow when fused together.
Page 1. Journal of System Design and Dynamics Vol.4, No.2, 2010 Autonomous Hovering and Landing o... more Page 1. Journal of System Design and Dynamics Vol.4, No.2, 2010 Autonomous Hovering and Landing of a Quad-rotor Micro Aerial Vehicle by Means of on Ground Stereo Vision System ∗ Dwi PEBRIANTI ∗∗ , Farid KENDOUL ∗∗∗ , Syaril AZRAD ∗∗ , ...
This paper describes an object tracking system using an autonomous micro air vehicle (MAV) and de... more This paper describes an object tracking system using an autonomous micro air vehicle (MAV) and demonstrate its potential use for civilian purposes. The vision-based control system relies on a color and feature based vision algorithm for target detection and tracking, Kalman filters for relative pose estimation, and a nonlinear controller for MAV stabilization and guidance. The vision algorithm relies on information from a single onboard camera. An arbitrary target can be selected in real-time from the ground control station, thereby outperforming template and learning-based approaches. Experimental results obtained from outdoor flight tests, showed that the vision-control system enabled the MAV to track and hover above the target as long as the battery is available.
Uploads
Papers by Syaril Azrad