Work

Multi-Robot Localization Using Relative Observations

Year: 2006

Type: conference-paper

Abstract: In this paper we consider the problem of simultaneously localizing all members of a team of robots. Each robot is equipped with proprioceptive sensors and exteroceptive sensors. The latter provide relative observations between the robots. Proprioceptive and exteroceptive data are fused with an Extended Kalman Filter. We derive the equations for this estimator for the most general relative observation between two robots. Then we consider three special cases of relative observations and we present the structure of the filter for each case. Finally, we study the performance of the approach through many accurate simulations.

Source: Proceedings - IEEE International Conference on Robotics and Automation/Proceedings

DOI: 10.1109/robot.2005.1570537

Authors: A. Martinelli, F. Pont, R. Siegwart

Institution: École Polytechnique Fédérale de Lausanne

Language: English

Topic: Robotics and Sensor-Based Localization

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Awards: Multisensor Fusion for Mobile Robot Simultaneous Localization, Mapping and Odometry Calibration, G993971353