Summary. Most estimation problems in robotics are difficult because of (a) the nonlinearity in observation models; and (b) the lack of suitable probabilistic models for the process and observation noise. In this paper we develop a set-valued approach to estimation that overcomes both these limitations and illustrates the application to localization of multiple, mobile sensor platforms with range sensors.
Stump et al., in REF , present a set-valued approach to estimation that overcomes limitations due to nonlinearities.
Extensive representations and algorithms for nonlinear filtering and estimation
In Proceedings of International Workshop on the Algorithmic Foundations of Robotics
Mathematics Computer Science