Lidar-Based Relative Position Estimation and Tracking for Multi-Robot Systems

Relative positioning systems play a vital role in current multi-robot systems. We present a self-contained detection and tracking approach, where a robot estimates a distance (range) and an angle (bearing) to another robot using measurements extracted from the raw data provided by two laser range finders. We propose a method based on the detection of circular features with least-squares fitting and filtering out outliers using a map-based selection. We improve the estimate of the relative robot position and reduce its uncertainty by feeding measurements into a Kalman filter, resulting in an accurate tracking system. We evaluate the performance of the algorithm in a realistic indoor environment to demonstrate its robustness and reliability.


Editor(s):
Reis, Luiz Paulo
Moreira, Antonio Paulo
Lima, Pedro U.
Montano, Luis
Munoz-Martinez, Victor
Published in:
Robot 2015: Second Iberian Robotics Conference, 1, 3-16
Presented at:
ROBOT'2015 - Second Iberian Robotics Conference, Lisbon, November 19-21, 2015
Year:
2015
Publisher:
Switzerland, Springer
ISBN:
978-3-319-27146-0
978-3-319-27145-3
Keywords:
Laboratories:




 Record created 2016-01-29, last modified 2018-05-09

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