Inferring a probability distribution function for the pose of a sensor network using a mobile robot

— In this paper we present an approach for localizing a sensor network augmented with a mobile robot which is capable of providing inter-sensor pose estimates through its odometry measurements. We present a stochastic algorithm that samples efficiently from the probability distribution for the pose of the sensor network by employing Rao-Blackwellization and a proposal scheme which exploits the sequential nature of odometry measurements. Our algorithm automatically tunes itself to the problem instance and includes a principled stopping mechanism based on convergence analysis. We demonstrate the favourable performance of our approach compared to that of established methods via simulations and experiments on hardware.

• Type: Conference
• Year: 2009
• Where: ICRA
• Authors: David Meger, Dimitri Marinakis, Ioannis M. Rekleitis, Gregory Dudek
• Keywords: ICRA 2009, Inter-sensor Pose Estimates, Odometry Measurements, Robotics, Sensor Network