Decentralized simultaneous localization and mapping for multiple aerial vehicles using range-only sensors

This paper presents an approach for decentralized range-only simultaneous localization and mapping (RO-SLAM) of a network of aerial vehicles and a set of static range-only sensors deployed in the environment. The paper makes use of a multi-hypothesis framework developed by the authors [1] in order to deal with the multiple hypotheses that are present in the early stages of the undelayed RO-SLAM, this paper extends the approach to consider the integration of landmark estimations provided by other aerial vehicles nearby the robot. The method will enable a significant reduction in the convergence time needed to remove wrong localization hypotheses for every range-only landmark and, as a results, a map with improved accuracy. The proposed approach is validated first in simulations and later on with real experiments involving real range-only sensors and two unmanned aerial vehicles.

[1]  K. Gulez,et al.  Evaluations of different Simultaneous Localization and Mapping (SLAM) algorithms , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[2]  Javier González,et al.  Efficient probabilistic Range-Only SLAM , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Fernando Caballero,et al.  Robust range-only SLAM for aerial vehicles , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).

[4]  D. Salmond.  Mixture reduction algorithms for target tracking , 1989 .

[5]  Sanjiv Singh,et al.  A Robust Method of Localization and Mapping Using Only Range , 2008, ISER.

[6]  Hui Zhang,et al.  Simultaneous localization and mapping of Robot in Wireless Sensor Network , 2010, 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[7]  Po Yang.  Efficient particle filter algorithm for ultrasonic sensor-based 2D range-only simultaneous localisation and mapping application , 2012, IET Wirel. Sens. Syst..

[8]  Stergios I. Roumeliotis,et al.  Decentralized multi-robot cooperative localization using covariance intersection , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[9]  Jeffrey K. Uhlmann,et al.  Using covariance intersection for SLAM , 2007, Robotics Auton. Syst..

[10]  Sanjiv Singh,et al.  Motion-Aided Network SLAM , 2010, ISER.

[11]  Aníbal Ollero,et al.  Undelayed 3D RO-SLAM based on Gaussian-mixture and reduced spherical parametrization , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[12]  Aníbal Ollero,et al.  A general Gaussian-mixture approach for range-only mapping using multiple hypotheses , 2010, 2010 IEEE International Conference on Robotics and Automation.

[13]  Wolfram Burgard,et al.  Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .

[14]  Aníbal Ollero,et al.  A particle filtering method for wireless sensor network localization with an aerial robot beacon , 2008, 2008 IEEE International Conference on Robotics and Automation.