Header logo is de

Cooperative Robot Localization and Target Tracking based on Least Squares Minimization

2013

Conference Paper

ps


In this paper we address the problem of cooperative localization and target tracking with a team of moving robots. We model the problem as a least squares minimization problem and show that this problem can be efficiently solved using sparse optimization methods. To achieve this, we represent the problem as a graph, where the nodes are robot and target poses at individual time-steps and the edges are their relative measurements. Static landmarks at known position are used to define a common reference frame for the robots and the targets. In this way, we mitigate the risk of using measurements and state estimates more than once, since all the relative measurements are i.i.d. and no marginalization is performed. Experiments performed using a set of real robots show higher accuracy compared to a Kalman filter.

Author(s): Ahmad, A and Tipaldi, GD and Lima, P and Burgard, W
Pages: 5696-5701
Year: 2013
Month: May
Publisher: IEEE

Department(s): Perzeptive Systeme
Bibtex Type: Conference Paper (inproceedings)

DOI: 10.1109/ICRA.2013.6631396
Event Name: IEEE International Conference on Robotics and Automation (ICRA 2013)
Event Place: Karlsruhe, Germany

BibTex

@inproceedings{AhmadTLB2013,
  title = {Cooperative Robot Localization and Target Tracking based on Least Squares Minimization},
  author = {Ahmad, A and Tipaldi, GD and Lima, P and Burgard, W},
  pages = {5696-5701},
  publisher = {IEEE},
  month = may,
  year = {2013},
  month_numeric = {5}
}