Tobias Schubert

Multi Robot Localization

Localization is one of the most fundamental tasks for mobile robots. For a team of multiple robots, a paradigm called Collaborative Localization (CL) has been demonstrated to provide significant improvements of the localization performance of the individual teammates. In CL, robots detect each other and communicate their estimates, which correlates the estimates of their individual poses. It is of fundamental importance to keep track of these dependencies to avoid the problem of double-counting or data-incest, which occurs when two robots treat shared information as uncorrelated.

In many relevant multi-robot applications -- for example underwater, in mines, or in large-scale environments, -- communication might be energy consuming, error-prone, slow, or simply not possible at all times. Therefore, decentralized architectures that reduce the need for communication to a minimum are desirable.

We restrict the communications to places where the robots actually meet. Thus, exchange of information takes place only between two robots obtaining a relative measurement. We developed an EKF-based localization algorithm that is able to approximate the covariance under the above-mentioned constraint.
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