Abstract
Autonomous environment mapping is an essential part of efficiently carrying out complex missions in unknown indoor environments. In this paper, a low cost mapping system composed of a web camera with structured light and sonar sensors is presented. We propose a novel exploration strategy based on the frontier concept using the low cost mapping system. Based on the complementary characteristics of a web camera with structured light and sonar sensors, two different sensors are fused to make a mobile robot explore an unknown environment with efficient mapping. Sonar sensors are used to roughly find obstacles, and the structured light vision system is used to increase the occupancy probability of obstacles or walls detected by sonar sensors. To overcome the inaccuracy of the frontier-based exploration, we propose an exploration strategy that would both define obstacles and reveal new regions using the mapping system. Since the processing cost of the vision module is high, we resolve the vision sensing placement problem to minimize the number of vision sensing in analyzing the geometry of the proposed sonar and vision probability models. Through simulations and indoor experiments, the efficiency of the proposed exploration strategy is proved and compared to other exploration strategies.
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Amigoni, F., Caglioti, V., Galtarossa, U.: A mobile robot mapping system with an information-based exploration strategy. In: Proceedings of the International Conference on Informatics in Control, Automation and Robotics (ICINCO2004), vol. 2, pp. 71–78 (2004)
Benjamin, T., et al.: Planning exploration strategies for simultaneous localization and mapping. Robotics and Autonomous Systems 54, 314–331 (2006)
Boyd, S., Vandenberghe, L.: Convex Optimization, pp. 432–438. Cambridge University Press (2004)
Chae, H., Lee, J., Yu, W., Doh, N.L.: StarLITE: a new artificial landmark for the navigation of mobile robots, Paper presented at the 1st Japan-Korea Joint Symposium on Network Robot Systems, Keihanna Science City, Kyoto, Japan, 25 November 2005
Elfes, A.: Using occupancy grids for mobile robot perception and navigation. IEEE Computer 22, 46–57 (1989)
Fisher, R.B., Ashbrook, A.P., Robertson, C., Werghi, N.: A low-cost range finder using a visually located, structured light source. In: Second International Conference 3-d Digital Imaging and Modeling, Ottawa, Ont., Canada, 4–8 Octbor 1999
Freda, L., Oriolo, G.: Frontier-based probabilistic strategies for sensor-based exploration. In: IEEE International Conference on Robotics and Automation, Barcelona, Spain, April 2005
Gonzalez-Banos, H.H., Latombe, J.-C.: Navigation strategies for exploring indoor environments. J. Robotics Res. 21(10–11), 829–848 (2004)
Grabowski, R., Khosla, P., Choset, H.: Autonomous exploration via region of interest. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, 27–31 October 2003
Kim, G.W., Kwak, N., Lee, B.H.: Low cost active range sensing using halogen sheet-of-light for occupancy grid map building. In: IEEE/RSJ International Conference on Robots and Systems, pp. 2288–2293, 2–6 August 2005
Kwak, N., Ji, S.H., Lee, B.H.: A knowledge base for dynamic path planning of multi-agents. Paper presented at the IFAC World Congress, Praha, Czech, 4–8 July 2005
Makarenko, A., Williams, S.B., Bourgault, F., Durrant-Whyhte, H.F.: An experiment in integrated exploration. In: IEEE/RSJ International Conference on Robots and Systems, EPFL, Lausanne, Switzland, October 2002
Moorehead, S.J., Simmons, R., Whittaker, W.L.: Autonomous exploration using multiple sources of information. In: IEEE International Conference on Robotics and Automation, Seoul, Korea, May 2001
Moravec, H.P.: Sensor fusion in certainty grids for mobile robots. AI magazine 9(2), 61–74 (1988)
Moshiri, B., Asharif, M.R., HoseinNezhad, R.: Pseudo information measure: a new concept for extention of Bayesian fusion in robotic map builing. Information Fusion 3, 51–68 (2002)
O’Beirne, D., Schukat, M.: Collaborative exploration for a group of self-interested robots. Canadian Conference on Computer and Robot Vision, pp. 184–191. IEEE Computer society (2005)
Oriolo, G., Venditelli, M., Freda, L., Troso, G.: The SRT method: randomized strategies for exploration. In: IEEE International Conference on Robotics and Automation, New Orleans, LA, 26 April–1 May 2004
Poncela, A., Perez, E.J., Bandera, A., Urdiales, C., Sandoval, F.: Efficient integration of metric and topological maps for directed exploration of unknown environments. Robotics and Autonomous Systems 41, 21–39 (2002)
Schultz, A.C., Adams, W., Yamauchi, B.: Integrating exploration, localization, navigation and planning with a common representation. Autonomous Robots 6, 293–308 (1999)
Shapiro, L.G., Stockman, G.C.: Computer vision. Prentice Hall (2001)
Stachniss, C., Burgard, W.: Mapping and exploration with mobile robots using coverage maps. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, 27–31 October 2003
Stachniss, C., Burgard, W.: Exploring unknown environments with mobile robots using coverage maps. In: International Joint Conference on Artificial Intelligence, pp. 1127–1134 (2003)
Stepan, P., Kulich, M., Preucil, L.: Robust data fusion with occupancy grid. IEEE Trans. Systems, Man, and Cybernetics-Part C, 35(1), 106–115 (2005)
Sujan, V.A., Dubowsky, S.: Efficient information-based visual robotic mapping in unstructured environments. J. Robotics Res. 24(4), 275–293 (2005)
Thrun, S., Burgard, W., Fox, D.: Probabilistic robotics. The MIT Press (2005)
Thrun, S., Bucken, A.: Integrating grid-based and topological maps for mobile robot navigation. In: Proceedings of the Thirteenth National Conference on Artificial Intelligence, vol. 2, pp. 944–950 (1996)
Tsai, C.C., Lin, H.H., Lai, S.W.: Multisensor 3D posture determination of a mobile robot using inertial and ultrasonic sensors. J. Intel. Robotic Syst. 42, 317–335 (2005)
Yamauchi, B.: A frontier-based approach for autonomous exploration. In: IEEE International Conference on Robotics and Automation, Monterey, CA, 10–11 July 1997
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Kwak, N., Kim, GW., Ji, SH. et al. A Mobile Robot Exploration Strategy with Low Cost Sonar and Tungsten-Halogen Structured Light. J Intell Robot Syst 51, 89–111 (2008). https://doi.org/10.1007/s10846-007-9178-1
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DOI: https://doi.org/10.1007/s10846-007-9178-1