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Cooperative N-Boundary Tracking in Large Scale Environments

Euler, Juliane and Horn, Andreas and Haumann, Dominik and Adamy, Jürgen and Stryk, Oskar von (2012):
Cooperative N-Boundary Tracking in Large Scale Environments.
Piscataway, NJ, USA, In: Proceedings of the IEEE 9th International Conference on Mobile Adhoc and Sensor Systems (MASS), Las Vegas, Nevada, USA, 8-11 Oct. 2012, Supplement, DOI: 10.1109/MASS.2012.6708518,
[Online-Edition: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6...],
[Conference or Workshop Item]

Abstract

Monitoring in large scale environments is a typ-ical mission in cooperative robotics. This task requires the exploration of a huge domain by a generally small number of sensor equipped mobile robots. As time restrictions prohibit an exhaustive global search, a sampling strategy is required that allows an efficient spatial mapping of the environment. This paper proposes an adaptive sampling strategy for efficient simultaneous tracking of multiple concentration levels of an atmospheric plume by a team of cooperating unmanned aerial vehicles (UAVs). The approach combines uncertainty and correlation-based concentration estimates to generate sampling points based on already gathered data. The adaptive generation of sampling locations is coupled to a distributed model-predictive controller for planning optimal vehicle trajectories under collision and communication constraints. Simulation results demonstrate that connectivity of all involved vehicles can be maintained and an accurate reconstruction of the plume is obtained efficiently.

Item Type: Conference or Workshop Item
Erschienen: 2012
Creators: Euler, Juliane and Horn, Andreas and Haumann, Dominik and Adamy, Jürgen and Stryk, Oskar von
Title: Cooperative N-Boundary Tracking in Large Scale Environments
Language: English
Abstract:

Monitoring in large scale environments is a typ-ical mission in cooperative robotics. This task requires the exploration of a huge domain by a generally small number of sensor equipped mobile robots. As time restrictions prohibit an exhaustive global search, a sampling strategy is required that allows an efficient spatial mapping of the environment. This paper proposes an adaptive sampling strategy for efficient simultaneous tracking of multiple concentration levels of an atmospheric plume by a team of cooperating unmanned aerial vehicles (UAVs). The approach combines uncertainty and correlation-based concentration estimates to generate sampling points based on already gathered data. The adaptive generation of sampling locations is coupled to a distributed model-predictive controller for planning optimal vehicle trajectories under collision and communication constraints. Simulation results demonstrate that connectivity of all involved vehicles can be maintained and an accurate reconstruction of the plume is obtained efficiently.

Volume: Supplement
Place of Publication: Piscataway, NJ, USA
Uncontrolled Keywords: adaptive sampling,boundary tracking,cooperative control,large scale environments
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Systems and Mechatronics
18 Department of Electrical Engineering and Information Technology > Institut für Automatisierungstechnik und Mechatronik > Control Methods and Robotics
20 Department of Computer Science
20 Department of Computer Science > Simulation, Systems Optimization and Robotics Group
Event Title: Proceedings of the IEEE 9th International Conference on Mobile Adhoc and Sensor Systems (MASS)
Event Location: Las Vegas, Nevada, USA
Event Dates: 8-11 Oct. 2012
Date Deposited: 20 Dec 2018 07:36
DOI: 10.1109/MASS.2012.6708518
Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6...
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