Abstract
Autonomous exploration under uncertain robot location requires the robot to use active strategies to trade-off between the contrasting tasks of exploring the unknown scenario and satisfying given constraints on the admissible uncertainty in map estimation. The corresponding problem, namely active SLAM (Simultaneous Localization and Mapping) and exploration, has received a large attention from the robotic community for its relevance in mobile robotics applications. In this work we tackle the problem of active SLAM and exploration with Rao-Blackwellized Particle Filters. We propose an application of Kullback-Leibler divergence for the purpose of evaluating the particle-based SLAM posterior approximation. This metric is then applied in the definition of the expected information from a policy, which allows the robot to autonomously decide between exploration and place revisiting actions (i.e., loop closing). Extensive tests are performed in typical indoor and office environments and on well-known benchmarking scenarios belonging to SLAM literature, with the purpose of comparing the proposed approach with the state-of-the-art techniques and to evaluate the maturity of truly autonomous navigation systems based on particle filtering.
Similar content being viewed by others
References
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)
Castellanos, J.A., Martinez-Cantin, R., Tardós, J.D., Neira, J.: Robocentric map joining: improving the consistency of EKF-SLAM. Robot. Auton. Syst. 55(1), 21–29 (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)
Martinez-Cantin, R., De Freitas, N., Castellanos, J.: Analysis of particle methods for simultaneous robot localization and mapping and a new algorithm: marginal-SLAM. In: Proc. of the IEEE lnternational Conf. on Robotics and Automation (2007)
Bourgault, F., Makarenko, A.A., Williams, S.B., Grocholsky, B., Durrant-Whyte, H.F.: Information based adaptive robotic exploration. In: Proc. of the IEEE-RSJ Int. Conf. on Intelligent Robots and Systems, pp. 540–545 (2002)
Martinez-Cantin, R., De Freitas, N., Doucet, A., Castellanos, J.A.: Active policy learning for robot planning and exploration under uncertainty. In: Proc. of Robotics: Science and Systems (2007)
Sim, R., Roy, N.: Global A-optimal robot exploration in SLAM. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 661–666 (2005)
Martinez-Cantin, R., De Freitas, N., Brochu, E., Castellanos, J., Doucet, A.: A Bayesian exploration-exploitation approach for optimal online sensing and planning with a visually guided mobile robot. Auton. Robot. 27(2), 93–103 (2009)
Carrillo, H., Reid, I., Castellanos, J.A.: On the comparison of uncertainty criteria for active SLAM. In: Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 2080–2087 (2012)
Valencia, R., Andrade-Cetto, J., Porta, J.M.: Path planning in belief space with pose SLAM. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 78–83 (2011)
Valencia, R., Valls Miró, J., Dissanayake, G., Andrade-Cetto, J.: Active pose SLAM. In: Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems, pp. 1885–1891 (2012)
Blanco, J.L., Fernandez-Madrigal, J.A., Gonzalez, J.: A novel measure of uncertainty for mobile robot SLAM with Rao-Blackwellized Particle Filters. Int. J. Robot. Res. 27(1), 73–89 (2008)
Carlone, L., Du, J., Kaouk Ng, M., Bona, B., Indri, M.: An application of Kullback-Leibler divergence to active SLAM and exploration with particle filters. In: Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems, pp. 287–293 (2010)
Carlone, L., Kaouk Ng, M., Du, J., Bona, B., Indri, M.: Reverse KLD-sampling for measuring uncertainty in Rao-Blackwellized Particle Filters SLAM. In: Proc. of the Workshop on Performance Evaluation and Benchmarking for Next Intelligent Robots and Systems. IEEE-RSJ Int. Conf. on Intelligent Robots and Systems (2009)
Du, J., Carlone, L., Kaouk Ng, M., Bona, B., Indri, M.: A comparative study on active SLAM and autonomous exploration with particle filters. In: Proc. of the IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, pp. 916–923 (2011)
Kullback, S., Leibler, A.: On information and sufficiency. Ann. Math. Stat. 22, 79–86 (1951)
Stachniss, C., Grisetti, G., Burgard, W.: Information gain-based exploration using Rao-Blackwellized Particle Filters. In: Proc. of Robotics: Science and Systems (2005)
Moravec, H.P.: Sensor fusion in certainty grids for mobile robots. AI Mag. 9(2), 61–74 (1988)
Yamauchi, B.: A frontier-based approach for autonomous exploration. In: Proc. of CIRA vol. 97, pp. 146–151 (1997)
Fox, D., Ko, J., Konolige, K., Limketkai, B., Schulz, D., Stewart, B.: Distributed multirobot exploration and mapping. Proc. IEEE 94(7), 1325–1339 (2006)
Moorehead, S.J., Simmons, R., Whitaker, W.L.: Autonomous exploration using multiple sources of information. In: Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 3098–3103 (2001)
Stachniss, C., Hahnel, D., Burgard, W.: Exploration with active loop-closing for FastSLAM. In: Proc. of the IEEE-RSJ Int. Conf. on Intelligent Robots and Systems, pp. 1505–1510 (2004)
Ko, J., Stewart, B., Fox, D., Konolige, K., Limketkai, B.: A practical decision-theoretic approach to multirobot mapping and exploration. In: Proc. of the IEEE-RSJ Int. Conf. on Intelligent Robotics and Systems, pp. 3232–3238 (2003)
Stachniss, C., Grisetti, G., Burgard, W.: Analyzing Gaussian proposal distributions for mapping with Rao-Blackwellized Particle Filters. In: Proc. of Int. Conf. on Intelligent Robots and Systems, pp. 3485–3490 (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)
Fox, D.: Adapting the sample size in particle filters through KLD-sampling. Int. J. Robot. Res. 22(12), 985–1003 (2003)
Carpin, S.: Fast and accurate map merging for multi-robot systems. Auton. Robot. 25(3), 305–316 (2008)
Howard, A.: Multi-robot simultaneous localization and mapping using particle filters. In: Proc. of Robotics: Science and Systems, pp. 201–208 (2006)
Roy, N., Burgard, W., Fox, D., Thrun, S.: Coastal navigation: mobile robot navigation with uncertainty in dynamic environments. In: Proc. of Int. Conf. on Robotics and Automation, pp. 35–40 (1999)
MobileRobots Inc.: MobileSim-the mobile robots simulator. http://www.robots.mobilerobots.com/MobileSim (2011). Accessed 10 Apr 2013
Robotics Research Group (RRG): Politecnico di Torino. http://www.polito.it/LabRob (2011). Accessed 10 Apr 2013
Kümmerle, R., Steder, B., Dornhege, C., Ruhnke, M., Grisetti, G., Stachniss, C., Kleiner, A.: Slam benchmarking webpage. http://ais.informatik.uni-freiburg.de/slamevaluation (2009). Accessed 10 Apr 2013
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Carlone, L., Du, J., Kaouk Ng, M. et al. Active SLAM and Exploration with Particle Filters Using Kullback-Leibler Divergence. J Intell Robot Syst 75, 291–311 (2014). https://doi.org/10.1007/s10846-013-9981-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-013-9981-9