Abstract
This paper gives a review of the literature on Simultaneous Localization and Mapping (SLAM). SLAM has been intensively researched in recent years in the field of robotics and intelligent vehicles, many approaches have been proposed including occupancy grid mapping method (Bayesian, Dempster-Shafer and Fuzzy Logic), Localization estimation method (edge or point features based direct scan matching techniques, probabilistic likelihood, particle filter). In this paper, we classify SLAM approaches into three main categories: visual SLAM, Lidar SLAM and sensor fusion SLAM, while visual and lidar can also contain many types and levels, such as monocular camera, stereovision, laser scanner, radar and fusion of these sensors. A number of promising approaches and recent developments in this literature have been reviewed in this paper. To give a better understanding of performance difference, an implementation of Lidar SLAM is presented with comparative analysis result.
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References
Ayache, N., Faugeras, O.D.: Building, registrating, and fusing noisy visual maps. International Journal of Robotics Research 7(6), 45–65 (1988)
Besl, P., Mckay, N.D.: A method for registration of 3D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)
Biber, P., Straser, W.: The normal distributions transform: A new approach to laser scan matching. In: IROS 2003, vol. 3, pp. 2743–2748 (2003)
Bosse, M., Rikoski, R., Leonard, J., Teller, S.: Vanishing points and 3d lines from omnidirectional video. In: ICIP 2002, vol. 3, pp. 513–516 (2002)
Bosse, M., Newman, P., Leonard, J., Teller, S.: Simultaneous localization and map building in large-scale cyclic environments using the Atlas framework. The International Journal of Robotics Research 23(12), 1113–1139 (2004)
Chen, Y., Medioni, G.: Object Modeling by Registration of Multiple RangeImage. In: Proc. IEEE Int. Conf. on Robotics and Automation (1991)
Cox, I.J.: Blanche.an experiment in guidance and navigation of an autonomous robot vehicle. IEEE Transactions on Robotics and Automation 7(2), 193–203 (1991)
Dailey, M.N., Parnichkun, M.: Landmark-based simultaneous localization and mapping with stereo vision. In: Proc. Asian Conference on Industrial Automation and Robotics, Bangkok, Thailand (2005)
Davison, A.J.: Real-time simultaneous localisation and mapping with a single camera. In: Proc. IEEE International Conference on Computer Vision, pp. 1403–1410 (2003)
Deans, M.: Bearing-Only Localization and Mapping. PhD thesis, tech. report CMU-RI-TR-05-41, Robotics Institute, Carnegie Mellon University (2005)
Diosi, A., Kleeman, L.: Laser scan matching in polar coordinates with application to SLAM. Intelligent Robots and Systems, 3317–3322 (2005)
Duckett, T., Saffiotti, A.: Building globally consistent gridmaps from topologies. In: Proc. of the 6th Int. IFAC Symp. on Robot Control, SyROCO, Austria (2000)
Eade, E., Drummond, T.: Scalable monocular SLAM. In: Proc. Conference on Computer Vision and Pattern Recognition, New York, USA, pp. 469–468 (2006)
Elfes, A.: Multi-source spatial data fusion using Bayesian reasoning. In: Abidi, M.A., Gonzalez, R.A. (eds.) Data fusion in robotics and machine intelligence, ch. 3. Academic Press, New York (1992)
Elinas, P., Sim, R.: Little. J.J.: SLAM: Stereo Vision SLAM Using the Rao-Blackwellised Particle Filter and a Novel Mixture Proposal Distribution. In: Proc. of ICRA 2006, pp. 1564–1570 (2006)
Fox, D., Burgard, W., Thrun, S.: Probabilistic methods for mobile robot mapping. In: Proc. of the IJCAI 1999 Workshop on Adaptive Spatial Representations of Dynamic Environments (1999)
Gambino, F., Oriolo, G., Ulivi, G.: Comparison of three uncertainty calculus techniques for ultrasonic map building. In: Proc. SPIE Int. Symp. on Aerospace/Defense Sensing and Control, vol. 2761, pp. 249–260 (1996)
Garcia, M.A., Solanas, A.: 3D Simultaneous Localization and Modeling from Stereo Vision. In: Proc. of ICRA 2004, pp. 847–853 (2004)
Groecke, R., Asthana, A., Pettersson, N., Petersson, L.: Visual vehicle egomotion estimation using the fourier-mellin transform. In: IEEE Intelligent Vehicles Symposium, Istanbul, pp. 450–455 (2007)
Guivant, J., Nebot, E., Baiker, S.: High accuracy navigation using laser range sensors in outdoor applications. In: IEEE Int. conf. on Robotics and automation, vol. 4, pp. 3817–3822 (2000)
Gutmann, J.S.: Robuste Navigation autonomer mobiler Systeme. PhD thesis, Universityy of Freiburg (2000)
Hahnel, D., Burgard, W., Fox, D., Thrun, S.: An efficient fastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements. In: IROS 2003, vol. 1, pp. 206–211 (2003)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision, 2nd edn. Cambridge University Press, Cambridge (2004)
Herath, D.C., Kodagoda, K.R.S., Dissanayake, G.: Stereo Vision Based SLAM: Issues and Solutions, Vision Systems. In: Obinata, G., Dutta, A. (eds.) Advanced Robotic Systems, pp. 565–582 (2007)
Iocchi, L., Konolige, K., Bajracharya, M.: Visually Realistic Mapping of a Planar Environment with Stereo. In: Proc. of ISER 2000 (2000)
Jeong, W.Y., Lee, K.M.: Visual SLAM with Line and Corner Features. In: Proc. of Intelligent Robots and Systems, pp. 2570–2575 (2006)
Lhuillier, M.: Automatic structure and motion using a catadioptric camera. In: IEEE Workshop on Omnidirectional Vision (2005)
Lingemann, K., Surmann, H., Nuchter, A., Hertzberg, J.: Indor and outdoor localization for fast mobile robots. In: IROS 2004, vol. 3, pp. 2185–2190 (2004)
Lu, F., Milios, E.E.: Robot pose estimation in unknown environments by matching 2D range scans. Computer Vision and Pattern Recognition, 935–938 (1994)
Lu, F.: Shape Registration Using Optimization for Mobile Robot Navigation. PhD thesis, University of Toronto (1995)
Milford, M.J., Wyeth, G.F.: Single camera vision-only slam on a suburban road network. In: IEEE International Conference on Robotics and Automation, ICRA 2008, pp. 3684–3689 (2008)
Milford, M.J., Prasser, D., Wyeth, G.: Ratslam: A hippocampal model for simultaneous localization and mapping. In: IEEE International Conference on Robotics and Automation, USA, pp. 403–408 (2004)
Moravec, H.P., Elfes, A.: High Resolution Maps from Wide Angle Sonar. In: Proceedings of the IEEE International Conference on Robotics and Automation, March 1985, pp. 116–121 (1985)
Moravec, H.: DARPA MARS program research progress. Carnegie Mellon University (2001), http://www.frc.ri.cmu.edu/hpm/talks/Report.0107.html
Murray, D., Little, J.J.: Using real-time stereo vision for mobile robot navigation. Autonomous Robots 8(2), 161–171 (2000)
Oriolo, G., Ulivi, G., Vendittelli, M.: Real-time map building and navigation for autonomous robots in unknow environments. IEEE Transactions on Systems, Man, and Cybernetics 5 (1999)
Pupilli, M., Calway, A.: Real-time camera tracking using a particle filter. In: Proc. British Machine Vision Conference, Oxford, UK, pp. 519–528 (2005)
Ribo, M., Pinz, A.: A comparison of three uncertainty calculi for building sonar-based occupancy grids. International Journal of Robotics and Autonomous Systems 35, 201–209 (2001)
Rosten, E., Drummond, T.: Fusing points and lines for high performance tracking. In: Proc. IEEE International Conference on Computer Vision, Beijing, China, pp. 1508–1515 (2005)
Scaramuzza, D., Fraundorfer, F., Siegwart, R.: Real-Time Monocular Visual Odometry for On-Road Vehicles with 1-Point RANSAC. In: Proceedings of the IEEE International Conference on Robotics and Automation, Japan, pp. 4293–4299 (2009)
Se, S., Lowe, D., Little, J.: Local and Global Localization for Mobile Robots using Visual Landmarks. In: Proc. of IROS 2001 (2001)
Tardif, J., Pavlidis, Y., Daniilidis, K.: Monocular visual odometry in urban environments using an omnidirectional camera. In: IEEE IROS, pp. 2531–2538 (2008)
Thrun, S., Burgard, W., Fox, D.: A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping. In: ICRA 2000, vol. 1, pp. 321–328 (2000)
Thrun, S.: Learning occupancy grids with forward sensor models. Autonomous robots 15, 111–127 (2003)
Tomono, M.: Robust 3D SLAM with a stereo Camera Based on an Edge-Point ICP Algorithm. In: IEEE International Conference on robotics and Automation, Japan, May 2009, pp. 4306–4311 (2009)
Tomono, M.: A scan matching method using euclidean invariant signature for global localization and map building. In: ICRA 2004, pp. 866–871 (2004)
Vu, T.D., Burlet, J., Aycard, O.: Mapping of environment, Detection and Tracking of Moving Objects using Occupancy Grids. In: Intelligent Vehicles Symposium, pp. 684–689. IEEE, Los Alamitos (2008)
Zhao, H., Shibasaki, R.: Reconstructing Urban 3D Model using Vehicle-borne Laser Range Scanners. In: Proc. of the Third Int. Conf. on 3-D Digital Imaging and Modeling, May 2001, pp. 349–356 (2001)
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Lu, Z., Hu, Z., Uchimura, K. (2009). SLAM Estimation in Dynamic Outdoor Environments: A Review. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds) Intelligent Robotics and Applications. ICIRA 2009. Lecture Notes in Computer Science(), vol 5928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10817-4_25
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DOI: https://doi.org/10.1007/978-3-642-10817-4_25
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