Abstract
This paper presents a real-time, low-computation trilateration model, designed for teams of cooperating mobile robots, working in unknown in-door environments without GPS signal accessibility. It allows to analytically build precision maps of the working area, giving information for the potential localization errors in each point of the space around the robots and thus simplifying movement planning and tracking. The technique relies on Time-Of-Flight measurements between several members of the team, used as static beacons, and the rest of the robots currently in motion. Simple parameter analysis is proposed for choosing the best suited robots to act as beacons for a given task. The performances of the mathematical and the statistical models have been validated numerically by computer simulations.
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Genchev, S., Venkov, P., Vidolov, B. (2008). Trilateration Analysis for Movement Planning in a Group of Mobile Robots. In: Dochev, D., Pistore, M., Traverso, P. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2008. Lecture Notes in Computer Science(), vol 5253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85776-1_30
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DOI: https://doi.org/10.1007/978-3-540-85776-1_30
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