Abstract
In this paper we investigate the problem of Simultaneous Localization and Mapping (SLAM) for a multi robot system. Relaxing some assumptions that characterize related work we propose an application of Rao-Blackwellized Particle Filters (RBPF) for the purpose of cooperatively estimating SLAM posterior. We consider a realistic setup in which the robots start from unknown initial poses (relative locations are unknown too), and travel in the environment in order to build a shared representation of the latter. The robots are required to exchange a small amount of information only when a rendezvous event occurs and to measure relative poses during the meeting. As a consequence the approach also applies when using an unreliable wireless channel or short range communication technologies (bluetooth, RFId, etc.). Moreover it allows to take into account the uncertainty in relative pose measurements. The proposed technique, which constitutes a distributed solution to the multi robot SLAM problem, is further validated through simulations and experimental tests.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Siciliano, B., Khatib, O.: Springer Handbook of Robotics. Springer (2008)
Fox, D.: Distributed multirobot exploration and mapping. In: Proc. of the 2nd Canadian Conference on Computer and Robot Vision (2006)
Durrant-Whyte, H., Bailey, T.: Simultaneous localisation and mapping (SLAM): part I. The essential algorithms. Robot. Autom. Mag. 13, 99–110 (2006)
Durrant-Whyte, H., Bailey, T.: Simultaneous localisation and mapping (SLAM): part II. State of the art. Robot. Autom. Mag. 13, 108–117 (2006)
Thrun, S.: A probabilistic online mapping algorithm for teams of mobile robots. Int. J. Rob. Res. 20(5), 335–363 (2001)
Williams, S., Durrant-Whyte, H.: Towards multi-vehicle simultaneous localisation and mapping. In: Proc. of the IEEE International Conference on Robotics and Automation (2002)
Stachniss, C.: Robotic mapping and exploration. In: Springer Tracts in Advanced Robotics, vol. 55. Springer (2009)
Zhou, X.S., Roumeliotis, S.I.: Multi robot SLAM map alignment with rendezvous. Technical Report, 2005-001 (2005)
Zhou, X.S., Roumeliotis, S.I.: Multi-robot SLAM with unknown initial correspondence: the robot rendezvous case. In: Proc. of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1785–1792 (2006)
Spanos, D.P., Olfati-Saber, R., Murray, R.: Approximate distributed Kalman filtering in sensor networks with quantifiable performance. In: Proc. of the 4th International Symposium on Information Processing in Sensor Networks, vol. 760, pp. 133–139 (2005)
Spanos, D.P., Olfati-Saber, R., Murray, R.: Distributed sensor fusion using dynamic Consensus. In: Proc. of the 16th IFAC World Congress (2005)
Thrun, S., Liu, Y.: Multi-robot SLAM with sparse extended information filters. In: Springer Tracts in Advanced Robotics, vol. 15, pp. 254–266 (2005)
Chang, H., Lee, C., Hu, Y., Lu, Y.: Multi-robot SLAM with topological/metric maps. In: Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (2007)
Carpin, S.: Fast and accurate map merging for multi-robot systems. Auton. Robots 25, 305–316 (2008)
Howard, A., Sukhatme, G.S., Mataric, M.J.: Multirobot simultaneous localization and mapping using manifold representations. In: Proc. of the IEEE, vol. 94, pp. 1360–1369 (2006)
Gutmann, J., Konolige, K.: Incremental mapping of large cyclic environments. In: Proc. of the 6th IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 318–325 (2000)
Howard, A.: Multi-robot simultaneous localization and mapping using particle filters. In: Robotics: Science and Systems, pp. 201–208 (2006)
Carlone, L., Kaouk Ng, M., Du, J., Bona, B., Indri, M.: Reverse KLD-sampling for measuring uncertainty in Rao-Blackwellized particle filters SLAM. In: Workshop on Performance Evaluation and Benchmarking for Next Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (2009)
Stachniss, C., Grisetti, G., Burgard, W., Roy, N.: Analyzing Gaussian proposal distributions for mapping with Rao-Blackwellized particle filters. In: Proc. of the International Conference on Intelligent Robots and Systems, pp. 3485–3490 (2007)
Grisetti, G., Tipaldi, G.D., Stachniss, C., Burgard, W., Nardi, D.: Fast and accurate SLAM with Rao-Blackwellized particle filters. J. Robot. Auton. Syst. 55, 30–38 (2007)
Doucet, A., de Freitas, J., Murphy, K., Russel, S.: Rao-Blackwellized particle filtering for dynamic bayesian networks. In. Proc. of the Conference on Uncertainty in Artificial Intelligence, pp. 176–183 (2000)
Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. MIT Press (2005)
Stachniss, C., Grisetti, G., Burgard, W.: Analyzing Gaussian proposal distributions for mapping with Rao-Blackwellized particle filters. In: Proc. of International Conference on Intelligent Robots and Systems (2007)
Arulampalam, S., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filter for on-line nonlinear/non-Gaussian bayesian tracking. IEEE Trans. Signal Process. 2(50), 174–188 (2002)
Stachniss, C., Grisetti, G., Hahnel, G., Burgard, W.: Improved Rao-Blackwellized mapping by adaptive sampling and active loop-closure. In: Proc. of the Workshop on Self-Organization of Adaptive behavior, pp. 1–15 (2004)
Lu, F., Milios, E.: Globally consistent range scan alignment for environment mapping. J. Auton. Robots 4, 333–349 (1997)
Mendez Polanco, J.A., Muñoz-Meléndez, A.: Collaborative robots for indoor environment exploration. In: 10th International Conference on Control, Automation, Robotics and Vision (2008)
Macchia, V., Rosa, S., Carlone, L., Bona, B.: An application of omnidirectional vision to grid-based SLAM in indoor environments. In: Proc. of the 2010 International Conference on Robotics and Automation, Workshop on Omnidirectional Robot Vision (2010)
Sagues, C., Murillo, A.C., Guerrero, J.J., Goedemé, T., Tuytelaars, T., Gool, L.V.: Localization with omnidirectional images using the 1d radial trifocal tensor. In: Proc. of the IEEE International Conference on Robotics and Automation, pp. 551–556 (2006)
Zhou, X., Roumeliotis, S.: Robot-to-robot relative pose estimation from range measurements. IEEE Trans. Robot. 24(6), 1379–1393 (2008)
Khan, Z., Balch, T., Dellaert, F.: A Rao-Blackwellized particle filter for eigentracking. In: Proc. of IEEE Computer Society Conference on Computer Vision and Pattern Recognition (2004)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
About this article
Cite this article
Carlone, L., Kaouk Ng, M., Du, J. et al. Simultaneous Localization and Mapping Using Rao-Blackwellized Particle Filters in Multi Robot Systems. J Intell Robot Syst 63, 283–307 (2011). https://doi.org/10.1007/s10846-010-9457-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-010-9457-0