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The International Journal of Robotics Research
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Predicting the Performance of Cooperative Simultaneous Localization and Mapping (C-SLAM)

Anastasios I. Mourikis

Dept. of Computer Science & Engineering, University of Minnesota, Minneapolis, MN 55455, mourikis{at}cs.umn.edu

Stergios I. Roumeliotis

Dept. of Computer Science & Engineering, University of Minnesota, Minneapolis, MN 55455, stergios{at}cs.umn.edu

In this paper we study the time evolution of the position estimates’ covariance in Cooperative Simultaneous Localization and Mapping (C-SLAM), and obtain analytical upper bounds for the positioning uncertainty. The derived bounds provide descriptions of the asymptotic positioning performance of a team of robots in a mapping task, as a function of the characteristics of the proprioceptive and exteroceptive sensors of the robots, and of the graph of relative position measurements recorded by the robots. A study of the properties of the Riccati recursion, which describes the propagation of uncertainty through time, yields (i) the guaranteed accuracy for a robot team in a given C-SLAM application, as well as (ii) the maximum expected steady-state uncertainty of the robots and landmarks, when the spatial distribution of features in the environment can be modeled by a known distribution. The theoretical results are validated both in simulation and experimentally.

Key Words: Cooperative SLAM • covariance bounds • SLAM performance characterization • Kalman filtering

The International Journal of Robotics Research, Vol. 25, No. 12, 1273-1286 (2006)
DOI: 10.1177/0278364906072515
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