{"title":"Robot Map Building from Sonar and Laser Information using DSmT with Discounting Theory","authors":"Xinde Li, Xinhan Huang, Min Wang","volume":7,"journal":"International Journal of Mechanical and Mechatronics Engineering","pagesStart":349,"pagesEnd":357,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/4001","abstract":"
In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.<\/p>\r\n","references":"[1] M. Montemerlo, S. Thrun, \"Simultaneous localization and mapping with\r\nunknown data association using Fast SLAM\", Presented at the 2003 IEEE\r\nInt. Conf. Robotics and Automation, pp.1985-1991.\r\n[2] A. J. Dasvison, D.W. Murray, \"Simultaneous localization and map\r\nbuilding using active vision\", IEEE Transactions on Pattern Analysis and\r\nMachine Intelligence, vol.24, no.7, 2002, pp. 865-880.\r\n[3] J. Bjom, S. Roland, \"Using EM to detect motion with mobile robots\",\r\nPresented at the 2003 IEEE\/RSJ Int. Conf Intelligent Robots and Systems,\r\npp.1518-1523, Las Vegas, Nevada.\r\n[4] D. Fox, W. Burgard, S. Thrun, \"Active markov localization for mobile\r\nrobots\", Robotics and Autonomous Systems, vol.25,no.12, 1998,\r\npp.195-207.\r\n[5] S. Thrun, D. Fox, W. Burgard, F. Dellaert, \"Robust monte carlo\r\nlocalization for mobile robots\", Artificial Intelligence, vol.128, 2001,\r\npp.99-141.\r\n[6] A. Elfes, H. Moravec, \"High resolution maps from wide angle sonar\",\r\nPresented at the 1985 IEEE Int Conf Robotics and Automation,\r\npp.116-121.\r\n[7] A. Elfes, \"Sonar-based real-world mapping and navigation\", IEEE\r\nJournal of Robotics Automat, Vol. 3, 1987, pp.249-265.\r\n[8] G.. Shafer, A mathematical theory of evidence. Princeton University\r\nPress, Princeton, NJ,1976.\r\n[9] D. Dubois, H. Prade, \"Representation and combination of uncertainty\r\nwith belief functions and possibility measures\", Computational\r\nIntelligence, vol.4, 1988, pp.244-264.\r\n[10] F. Smarandache, J. Dezert (Editors)( 2004), Advances and Applications\r\nof DSmT for Information Fusion, American Research Press, Rehoboth, ,\r\nAvailable: http:\/\/www.gallup.unm.edu\/~smarandache\/DSmT- book1.pdf\r\n[11] J. Dezert, F. Smarandache, \"On the generation of hyper-power sets for the\r\nDSmT\", Presented at the 2003 Int. Conf. Information Fusion,\r\npp.1118-1125, FUSION 2003, Cairns, Queensland, Australia.\r\n[12] J. Dezert, F. Smarandache, \"Partial ordering of hyper-power sets and\r\nmatrix representation of belief functions within DSmT\", Presented at the\r\n2003 Int. Conf. Information Fusion, pp.1230-1238, FUSION 2003,\r\nCairns, Queensland, Australia .\r\n[13] E.Lefevre, O. Colot, P. Vannoorenberghe, \"Belief functions combination\r\nand conflict management\", Information Fusion Journal, vol. 3, no.2, 2002,\r\npp.149-162.\r\n[14] Ph. Smets, \"Data fusion in the transferable belief model\", Presented at the\r\n2000 Int. Conf. Information Fusion , Paris.\r\n[15] W.H. Wang, \"Map building by mobile robots in unknown environment\",\r\nPh.D. Thesis, Dept. auto, Shanghai Jiao Tong University, 2003.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 7, 2007"}