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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nageli, T. Conte, C. Domahidi, A. Morari, M. Hilliges, O. |
| Copyright Year | 2014 |
| Description | Author affiliation: Dept. of Inf. Technol. & Electr. Eng., ETH Zurich, Zurich, Switzerland (Conte, C.; Morari, M.) || Dept. of Comput. Sci., ETH Zurich, Zurich, Switzerland (Nageli, T.; Hilliges, O.) || Inspire AG, Zurich, Switzerland (Domahidi, A.) |
| Abstract | Some aerial tasks are achieved more efficiently and at a lower cost by a group of independently controlled micro aerial vehicles (MAVs) when compared to a single, more sophisticated robot. Controlling formation flight can be cast as a two-level problem: stabilization of relative distances of agents (formation shape control) and control of the center of gravity of the formation. To date, accurate shape control of a formation of MAVs usually relies on external tracking devices (e.g. fixed cameras) or signals (e.g. GPS) and uses centralized control, which severely limits its deployment. In this paper, we present an environment-independent approach for relative MAV formation flight, using a distributed control algorithm which relies only on embedded sensing and agentto- agent communication. In particular, an on-board monocular camera is used to acquire relative distance measurements in combination with a consensus-based distributed Kalman filter. We evaluate our methods in- and outdoors with a formation of three MAVs while controlling the formation's center of gravity manually. |
| Starting Page | 1141 |
| Ending Page | 1146 |
| File Size | 5076696 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781479969340 |
| DOI | 10.1109/IROS.2014.6942701 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-14 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bismuth Vectors Cameras Gravity Robot sensing systems Kalman filters Global Positioning System |
| Content Type | Text |
| Resource Type | Article |
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