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| Content Provider | Springer Nature Link |
|---|---|
| Author | Saska, Martin Krajník, Tomáš Vonásek, Vojtěch Kasl, Zdeněk Spurný, Vojtěch Přeučil, Libor |
| Copyright Year | 2013 |
| Abstract | A fault-tolerant method for stabilization and navigation of 3D heterogeneous formations is proposed in this paper. The presented Model Predictive Control (MPC) based approach enables to deploy compact formations of closely cooperating autonomous aerial and ground robots in surveillance scenarios without the necessity of a precise external localization. Instead, the proposed method relies on a top-view visual relative localization provided by the micro aerial vehicles flying above the ground robots and on a simple yet stable visual based navigation using images from an onboard monocular camera. The MPC based schema together with a fault detection and recovery mechanism provide a robust solution applicable in complex environments with static and dynamic obstacles. The core of the proposed leader-follower based formation driving method consists in a representation of the entire 3D formation as a convex hull projected along a desired path that has to be followed by the group. Such an approach provides non-collision solution and respects requirements of the direct visibility between the team members. The uninterrupted visibility is crucial for the employed top-view localization and therefore for the stabilization of the group. The proposed formation driving method and the fault recovery mechanisms are verified by simulations and hardware experiments presented in the paper. |
| Starting Page | 603 |
| Ending Page | 622 |
| Page Count | 20 |
| File Format | |
| ISSN | 09210296 |
| Journal | Journal of Intelligent & Robotic Systems |
| Volume Number | 73 |
| Issue Number | 1-4 |
| e-ISSN | 15730409 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2013-10-12 |
| Publisher Place | Dordrecht |
| Access Restriction | Subscribed |
| Subject Keyword | Mobile robots Micro aerial vehicles Formation driving Fault detection and recovery Model predictive control Leader-follower Trajectory planning Control, Robotics, Mechatronics Electrical Engineering Artificial Intelligence (incl. Robotics) Mechanical Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Industrial and Manufacturing Engineering Artificial Intelligence Control and Systems Engineering Mechanical Engineering Electrical and Electronic Engineering Software |
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