Roumeliotis S. I., Bekey, G.A.:

"Synergetic Localization for Groups of Mobile Robots "

 


Abstract:

In this paper we present a new approach to the problem of simultaneously localizing a group of mobile robots capable of sensing each other. Each of the robots col­ lects sensor data regarding its own motion and shares this information with the rest of the team during the update cycles. A single estimator, in the form of a Kalman filter, processes the available positioning infor­ mation from all the members of the team and produces a pose estimate for each of them. The equations for this centralized estimator can be written in a decentral­ ized form therefore allowing this single Kalman filter to be decomposed into a number of smaller communi­ cating filters each of them processing local (regarding the particular host robot) data for most of the time. The resulting decentralized estimation scheme consti­ tutes a unique mean for fusing measurements collected from a variety of sensors with minimal communication and processing requirements. The distributed localiza­ tion algorithm is applied to a group of 3 robots and the improvement in localization accuracy is presented. Finally, a comparison to the equivalent distributed in­ formation filter is provided.

 


 

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