Warianty tytułu
Semantic navigation
Języki publikacji
Abstrakty
W poniższej pracy przedstawiono system nawigacyjny robota mobilnego. W procesie planowania trasy wykorzystuje się semantyczną wiedzę o otoczeniu. Robot wyposażony w skaner laserowy 3D analizuje otoczenie i przypisuje obserwowanym obiektom etykiety. Cel do którego robot ma dotrzeć jest wskazywany poprzez podanie nazwy obiektu. Możemy więc wydać polecenie typu jedź do ściany, do drzwi, czy też umywalki. Zastosowano hybrydową rastrowo-obiektową reprezentację otoczenia. W procesie planowania trasy zastosowano sieci komórkowe.
In this article we present a system which allows a mobile robot to navigate in an outdoor or indoor environment. Data obtained from a 3D laser range finder is analyzed and semantic labels are attached to the detected objects. The dual grid based and semantic map is built. The obstacle-free path is generated using a Cellular Neural Network. The goal for the robot is given using semantic labels. When the same label is attached to many objects the cheapest path is found. The path planning method is fast and allows taking into account various features of the environment and types of robots. In comparison to the potential field method the algorithm proposed in this paper does not suffer from local minima problem. The experiments were performed in real indoor and outdoor environments.
Rocznik
Tom
Strony
645-654
Opis fizyczny
Bibliogr. 21 poz., rys.
Twórcy
autor
autor
autor
autor
- Politechnika Warszawska, Instytut Automatyki i Robotyki, IPPT PAN, bsiem@ippt.gov.pl
Bibliografia
- [1] B. Barraquand, J. C. Langois, J. C. Latombe. Numerical potential field techniques for robot path planning. IEEE Transactions on Robotics and Automation, Man and Cybernetics, 1992, wolumen 22, s. 224-241.
- [2] R. E. Bellman. Dynamic Programming. Princeton University Press 1957.
- [3] M. Bennewitz, W. Burgard, S. Thrun. Optimizing schedules for prioritized path planning of multi-robot systems. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 2000.
- [4] S. J. Buckley. Fast motion planning for multiple moving robots. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 1989, s. 1419-1424.
- [5] H. Chu, H. A. Eimaraghy. Real-time multi-robot path planner based on a heuristic approach. In Proc. of the IEEE International Conference on Robotics & Automation (ICRA), 1992.
- [6] L. Chua, T. Roska. The cnn paradigm. IEEE Transaction on Circuit Systems, 1993, wolumen 40, s. 147-156.
- [7] L. Chua, L. Young. Cellular neural network. IEEE Transaction on Circuit System, 1988, wolumen 35, s. 1271-1290.
- [8] M. Gnatowski, B. Siemiątkowska, R. Chojecki. Building three dimensional maps based on cellular neural networks. WSEAS Transaction on Computers, 2008, wolumen 7, s. 1040-1049.
- [9] B. Krose, O. Booij, Z. Zivkovic. A geometrically constrained images similarity measure for visual mapping, localization and navigation. In: Proceedings of the 34d ECMR. Proceedings. Red. W. Burgard, H. M. Gross, 2007, s. 168-173.
- [10] J. C. Latombe. Robot Motion Planning. Kluwer Academic Publishers. MA Boston 1992.
- [11] S. P. Meyn. Control Techniques for Complex Networks. Cambridge University Press 2007.
- [12] H. Moravec, A. Elfes. High resolution maps from wide angle sonar. Proc. IEEE International Conference on Robotics and Automation, 1985, s. 116-121.
- [13] O. M. Mozos et al. Supervised semantic labeling of places using information extracted from sensor data. Robotics and Autonomous Systems, 2007, wolumen 5, s. 392-402.
- [14] M. Pfingsthorn, B. Slamet, A. Visser. A scalable hybrid multi-robot slam method for highly detailed maps. In: Proceedings of the 11th RoboCup International Symposium. Proceedings, 2007.
- [15] E. Remolina, B. Kuipers. Towards a general theory of topological maps. Artificial Intelligence, 2004, wolumen 152, numer 1, s. 47-104.
- [16] R. B. Rusu et al. Towords 3d point cloud based object maps for household environment. Journal of Robotics and Autonomous Systems, 2008, wolumen 56, s. 927-941.
- [17] B. Siemiątkowska et al. Towards semantic navigation system. In: Recent Advances in Intelligent Information Systems. Proceedings. Red. M. Klopotek et al. Exit, 2009, s. 711-720.
- [18] B. Siemiątkowska et al. Budowa hybrydowej semantyczno-rastrowej reprezentacji otoczenia robota mobilnego na podstawie wskazań dalmierza laserowego 3d. Pomiary Automatyka Kontrola, 2010, wolumen 3, s. 279-282.
- [19] B. Siemiątkowska et al. Segmentacja danych otrzymanych z lasera 3d. Pomiary Automatyka Kontrola, 2010, wolumen 3, s. 275-278.
- [20] S. Thrun, W. Burgard, D. Fox. Probabilistic Robotics (Intelligent Robotics and Autonomous Agents). The MIT Press 2005.
- [21] G. Vosselman et al. Recognizing structure in laser scanner point clouds. In: Proceedings of Conference on Laser scanners for Forest and Landscape assessment and instruments. Proceedings, 2004.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA9-0046-0029