Abstract
In this paper a generic approach to the SLAM (Simultaneous Localization and Mapping) problem is proposed. The approach is based on a probabilistic SLAM algorithm and employs only two portable sensors, an inertial measurement unit (IMU) and a laser range finder (LRF) to estimate the state and environment of a robot. Scan-matching is applied to compensate for noisy IMU measurements. This approach does not require any robot-specific characteristics, e.g. wheel encoders or kinematic models. In principle, this minimal sensory setup can be mounted on different robot systems without major modifications to the underlying algorithms. The sensory setup with the probabilistic algorithm is tested in real-world experiments on two different kinds of robots: a simple two-wheeled robot and the six-legged hexapod AMOSII. The obtained results indicate a successful implementation of the approach and confirm its generic nature. On both robots, the SLAM problem can be solved with reasonable accuracy.
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References
Wooden, D., Malchano, M., Blankespoor, K., Howardy, A., Rizzi, A.A., Raibert, M.: Autonomous navigation for bigdog. In: 2010 IEEE International Conference on Robotics and Automation (ICRA), pp. 4736–4741 (May 2010)
Burgard, W., Cremers, A.B., Fox, D., Hähnel, D., Lakemeyer, G., Schulz, D., Steiner, W., Thrun, S.: Experiences with an interactive museum tour-guide robot. Artificial Intelligence 114(1–2), 3–55 (1999)
Jones, J.L., Mack, N.E., Nugent, D.M., Sandin, P.E.: Autonomous floor-cleaning robot (August 27, 2013). US Patent 8,516,651
Sandin, P.E., Jones, J.L., et al.: Lawn care robot (January 21, 2014). US Patent 8,634,960
Wieser, I., Ruiz, A.V., Frassl, M., Angermann, M., Mueller, J., Lichtenstern, M.: Autonomous robotic slam-based indoor navigation for high resolution sampling with complete coverage. In: Position, Location and Navigation Symposium-PLANS 2014, 2014 IEEE/ION, pp. 945–951 (2014)
Müller, J.: Autonomous navigation for miniature indoor airships. PhD thesis, Universitätsbibliothek Freiburg (2013)
Grzonka, S., Grisetti, G., Burgard, W.: A fully autonomous indoor quadrotor. IEEE Transactions on Robotics 28(1), 90–100 (2012)
Kwak, N., Stasse, O., Foissotte, T., Yokoi, K.: 3d grid and particle based slam for a humanoid robot. In: 9th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2009, pp. 62–67 (2009)
Davison, A.J., Reid, I.D., Molton, N.D., Stasse, O.: Monoslam: Real-time single camera slam. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(6), 1052–1067 (2007)
Kim, A., Eustice, R.M.: Real-time visual slam for autonomous underwater hull inspection using visual saliency. IEEE Transactions on Robotics (2013)
Stasse, O., Davison, A.J., Sellaouti, R., Yokoi, K.: Real-time 3d slam for humanoid robot considering pattern generator information. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 348–355 (2006)
Belter, D., Skrzypczynski, P.: Precise self-localization of a walking robot on rough terrain using parallel tracking and mapping. Industrial Robot: An International Journal 40(3), 229–237 (2013)
Bloesch, M., Hutter, M., Hoepflinger, M.A., Leutenegger, S., Gehring, C., Remy, C.D., Siegwart, R.: State estimation for legged robots-consistent fusion of leg kinematics and imu. Robotics 17 (2013)
Wawrzyński, P., Możaryn, J., Klimaszewski, J.: Robust estimation of walking robots velocity and tilt using proprioceptive sensors data fusion. Robotics and Autonomous Systems (2014)
Thrun, S., Burgard, W., Fox, D.: Probabilistic robotics. MIT Press (2005)
Diosi, A., Kleeman, L.: Fast laser scan matching using polar coordinates. The International Journal of Robotics Research 26(10), 1125–1153 (2007)
Bresenham, J.E.: Algorithm for computer control of a digital plotter. IBM Systems Journal 4(1), 25–30 (1965)
Jones, J.L.: RugWarriorPro: Assembly guide. AK Peters Ltd. (1999)
Manoonpong, P., Parlitz, U., Wörgötter, F.: Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines. Frontiers in Neural Circuits (2013)
Kümmerle, R., Ruhnke, M., Steder, B., Stachniss, C., Burgard, W.: Autonomous robot navigation in populated pedestrian zones. Journal of Field Robotics (2014)
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Kesper, P., Berscheid, L., Wörgötter, F., Manoonpong, P. (2015). A Generic Approach to Self-localization and Mapping of Mobile Robots Without Using a Kinematic Model. In: Dixon, C., Tuyls, K. (eds) Towards Autonomous Robotic Systems. TAROS 2015. Lecture Notes in Computer Science(), vol 9287. Springer, Cham. https://doi.org/10.1007/978-3-319-22416-9_15
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DOI: https://doi.org/10.1007/978-3-319-22416-9_15
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