Planning for Multi-robot Localization
This paper will present a cooperative multi-robot localization model with planning support. Models of communication and transmission of pose estimates are constantly explored, however how the robots act on the environment is generally defined by random actions (from the localization task’s point of view). Random actions generate observations that can be useless for improving the estimate. This work describes a proposal for multi-robot localization with planning of actions. The objective is to describe a model where policies define the best action to performed by robots. The proposed model, called Model of Planned Localization - MPL, uses POMDPs to model the problems of location and specific algorithms to generate policies. We compared the MPL to a model that does not make use of planning actions. The results showed that MPL is able to estimate the positions of robots with lower number of steps, being more efficient than model compared.
KeywordsMulti-robot localization POMDP Planning Markov localization
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