Reference : Computer vision based general object following for GPS-denied multirotor unmanned vehicles
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Electrical & electronics engineering
http://hdl.handle.net/10993/45807
Computer vision based general object following for GPS-denied multirotor unmanned vehicles
English
Pestana, Jesus []
Sanchez Lopez, Jose Luis mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > Automation >]
Saripalli, Srikanth []
Campoy, Pascual []
Jun-2014
2014 American Control Conference
1886-1891
Yes
No
International
2014 American Control Conference
from 04-06-2014 to 06-06-2014
[en] The motivation of this research is to show that visual based object tracking and following is reliable using a cheap GPS-denied multirotor platform such as the AR Drone 2.0. Our architecture allows the user to specify an object in the image that the robot has to follow from an approximate constant distance. At the current stage of our development, in the event of image tracking loss the system starts to hover and waits for the image tracking recovery or second detection, which requires the usage of odometry measurements for self stabilization. During the following task, our software utilizes the forward-facing camera images and part of the IMU data to calculate the references for the four on-board low-level control loops. To obtain a stronger wind disturbance rejection and an improved navigation performance, a yaw heading reference based on the IMU data is internally kept and updated by our control algorithm. We validate the architecture using an AR Drone 2.0 and the OpenTLD tracker in outdoor suburban areas. The experimental tests have shown robustness against wind perturbations, target occlusion and illumination changes, and the system's capability to track a great variety of objects present on suburban areas, for instance: walking or running people, windows, AC machines, static and moving cars and plants.
http://hdl.handle.net/10993/45807
10.1109/ACC.2014.6858831

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