Abstract
This paper tackles the problem of coordinated vision-based tracking of a ground target by a fleet of multiple UAVs that exchange information over a supporting time-varying network. The objective of this work is to formulate decentralized control algorithms that enable multiple vehicles to follow a target while coordinating their phase separation. A typical scenario involves multiple aerial surveillance UAVs which are required to monitor a moving ground object (target tracking), while maintaining a desired inter-vehicle separation (coordination). To solve the tracking problem, the yaw rate of each vehicle is used as control input, while the ground speeds are adjusted to achieve coordination. It is assumed that the UAVs are equipped with an internal autopilot, which is able to track yaw rate and ground speed commands. The performance of the coordinated vision-based tracking algorithm is evaluated as a function of target's velocity, tracking performance of the onboard autopilot, and the quality of service of the communication network.
| Original language | English (US) |
|---|---|
| Title of host publication | IROS Hamburg 2015 - Conference Digest |
| Subtitle of host publication | IEEE/RSJ International Conference on Intelligent Robots and Systems |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 656-661 |
| Number of pages | 6 |
| Volume | 2015-December |
| ISBN (Electronic) | 9781479999941 |
| DOIs | |
| State | Published - Dec 11 2015 |
| Event | IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 - Hamburg, Germany Duration: Sep 28 2015 → Oct 2 2015 |
Other
| Other | IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2015 |
|---|---|
| Country | Germany |
| City | Hamburg |
| Period | 9/28/15 → 10/2/15 |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications
Cite this
Coordinated vision-based tracking for multiple UAVs. / Cichella, Venanzio; Kaminer, Isaac; Dobrokhodov, Vladimir; Hovakimyan, Naira.
IROS Hamburg 2015 - Conference Digest: IEEE/RSJ International Conference on Intelligent Robots and Systems. Vol. 2015-December Institute of Electrical and Electronics Engineers Inc., 2015. p. 656-661 7353442.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Coordinated vision-based tracking for multiple UAVs
AU - Cichella, Venanzio
AU - Kaminer, Isaac
AU - Dobrokhodov, Vladimir
AU - Hovakimyan, Naira
PY - 2015/12/11
Y1 - 2015/12/11
N2 - This paper tackles the problem of coordinated vision-based tracking of a ground target by a fleet of multiple UAVs that exchange information over a supporting time-varying network. The objective of this work is to formulate decentralized control algorithms that enable multiple vehicles to follow a target while coordinating their phase separation. A typical scenario involves multiple aerial surveillance UAVs which are required to monitor a moving ground object (target tracking), while maintaining a desired inter-vehicle separation (coordination). To solve the tracking problem, the yaw rate of each vehicle is used as control input, while the ground speeds are adjusted to achieve coordination. It is assumed that the UAVs are equipped with an internal autopilot, which is able to track yaw rate and ground speed commands. The performance of the coordinated vision-based tracking algorithm is evaluated as a function of target's velocity, tracking performance of the onboard autopilot, and the quality of service of the communication network.
AB - This paper tackles the problem of coordinated vision-based tracking of a ground target by a fleet of multiple UAVs that exchange information over a supporting time-varying network. The objective of this work is to formulate decentralized control algorithms that enable multiple vehicles to follow a target while coordinating their phase separation. A typical scenario involves multiple aerial surveillance UAVs which are required to monitor a moving ground object (target tracking), while maintaining a desired inter-vehicle separation (coordination). To solve the tracking problem, the yaw rate of each vehicle is used as control input, while the ground speeds are adjusted to achieve coordination. It is assumed that the UAVs are equipped with an internal autopilot, which is able to track yaw rate and ground speed commands. The performance of the coordinated vision-based tracking algorithm is evaluated as a function of target's velocity, tracking performance of the onboard autopilot, and the quality of service of the communication network.
UR - http://www.scopus.com/inward/record.url?scp=84958169289&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84958169289&partnerID=8YFLogxK
U2 - 10.1109/IROS.2015.7353442
DO - 10.1109/IROS.2015.7353442
M3 - Conference contribution
AN - SCOPUS:84958169289
VL - 2015-December
SP - 656
EP - 661
BT - IROS Hamburg 2015 - Conference Digest
PB - Institute of Electrical and Electronics Engineers Inc.
ER -