Scalable cooperative localization with minimal sensor configuration

Abstract

Localization of distributed robots can be improved by fusing the sensor data from each robot collectively in the network. This may allow for each individual robot’s sensor configuration to be reduced while maintaining an acceptable level of uncertainty. However, the scalability of a reduced sensor configuration should be carefully considered lest the propagated error become unbounded in large networks of robots. In this paper, we propose a minimal but scalable sensor configuration for a fleet of vehicles localizing on the urban road. The cooperative localization is proven to be scalable if the sensors’ data are informative enough. The experimental results justify that pose uncertainty will remain at an acceptable level when the number of robots increases.