Skip to the main content

Automatika : journal for control, measurement, electronics, computing and communications, Vol. 58 No. 1, 2017.

Original scientific paper

https://doi.org/10.1080/00051144.2017.1372123

Cooperative SLAM for multiple UGVs navigation using SVSF filter

Fethi Demim ; Laboratoire Robotique et Productique, Ecole Militaire Polytechnique (EMP), Algiers, Algeria
Abdelkrim Nemra ; Laboratoire Robotique et Productique, Ecole Militaire Polytechnique (EMP), Algiers, Algeria
Kahina Louadj ; Laboratoire LIMPAF, Universite de Bouira, Algeria
Mustapha Hamerlain ; Division Productique et Robotique, Center for Development of Advanced Technologies (CDTA), Algiers, Algeria
Abdelouahab Bazoula ; Laboratoire Robotique et Productique, Ecole Militaire Polytechnique (EMP), Algiers, Algeria

Full text: english pdf 2.019 Kb

page 119-129

downloads: 499

cite

Abstract

The aim of this paper is to present a cooperative simultaneous localization and mapping (CSLAM) solution based on a laser telemeter. The proposed solution gives the opportunity to a group of unmanned ground vehicles (UGVs) to construct a large map and localize themselves without any human intervention. Many solutions proposed to solve this problem, most of them are based on the sequential probabilistic approach, based around Extended Kalman Filter (EKF)
or the Rao-Blackwellized particle filter. In our work, we propose a new alternative to avoid these limitations, a novel alternative solution based on the smooth variable structure filter (SVSF) to solve the UGV SLAM problem is proposed. This version of SVSF-SLAM algorithm uses a boundary layer width vector and does not require covariance derivation. The new algorithm has been developed to implement the SVSF filter for CSLAM. Our contribution deals with adapting the SVSF to solve the CSLAM problem for multiple UGVs. The algorithms developed in this work were implemented using a swarm of mobile robots Pioneer 3–AT. Two mapping approaches, point-based and line-based, are implemented and validated experimentally using 2D laser telemeter sensors. Good results are obtained by the Cooperative SVSF-SLAM algorithm compared with the Cooperative EKF-SLAM.

Keywords

Localization; map building; SVSF filter; sensor fusion; autonomous navigation; cooperative SLAM; mobile robots

Hrčak ID:

203348

URI

https://hrcak.srce.hr/203348

Publication date:

19.9.2017.

Visits: 1.354 *