Abstract
Searching for an object in an environment using a mobile robot is a challenging task that requires an algorithm to define a set of points in which to sense the environment and an effective traversing strategy, to decide the order in which to visit such points. Previous work on sensing strategies normally assume unrealistic conditions like infinite visibility of the sensors. This paper introduces the concept of recognition area that considers the robot’s perceptual limitations. Three new sensing algorithms using the recognition area are proposed and tested over 20 different maps of increasing difficulty and their advantages over traditional algorithms are demonstrated. For the traversing strategy, a new heuristic is defined that significantly reduces the branching factor of a modified Branch & Bound algorithm, producing paths which are not too far away from the optimal paths but with several orders of magnitude faster that a traditional Branch & Bound algorithm.
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References
Baxter, J.L., Norman, M.: Multi-robot search and rescue: A potential field based approach
Casper, J., Murphy, R.: Human-robot interaction during the robot-assited urban search and rescue effort at the world trade center. IEEE Transactions on Systems, Man and Cybernetics Parts B 33(3), 367–385 (2003)
Eberly, D.: Triangulation by ear clipping (March 2008)
Hoffmann, F., Kaufmann, M., Kriegel, K.: The art gallery theorem for polygons with holes. In: The 32nd IEEE Symposium on the Foundation of Computer Science, pp. 39–48 (1991)
Latombe, J.C.: Robot motion planning, Boston (1991)
Nourbakhsh, I.R., Sycara, K., Koes, M., Yong, M., Lewis, M., Burion, S.: Human-robot teaming for search and rescue. IEEE CS and IEEE ComSoc (2005)
O’Rourke, J.: Art gallery theorems and algorithms. Oxford University Press Inc., New York (1987)
O’Rourke, J.: Computational Geometry in C. Cambridge University Press, Cambridge (1998) Hardback ISBN: 0521640105; Paperback: ISBN 0521649765
Sarmiento, A., Murrieta-Cid, R., Hutchinson, S.: An efficient strategy for rapidly finding an object in a polygonal world. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1153–1158 (2003)
Sarmiento, A., Murrieta-Cid, R., Hutchinson, S.: A sample-based convex cover for rapidly finding an object in a 3-d environment. In: Proc. IEEE International Conference on Robotics and Automation, pp. 3497–3502 (2005)
Sjöö, K., Galvez-Lopez, D., Paul, C., Jensfelt, P., Kragic, D.: Object search and localization for an indoor mobile robot. Journal of Computing and Information Technology - CIT 17(1), 67–80 (2009)
Tovar, B., LaValle, S.M., Murrieta-Cid, R.: Optimal navigation and object finding without geometric maps or localization. In: Proc. IEEE International Conference on Robotics and Automation, pp. 464–470 (2003)
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Cabanillas, J., Morales, E.F., Sucar, L.E. (2010). An Efficient Strategy for Fast Object Search Considering the Robot’s Perceptual Limitations. In: Kuri-Morales, A., Simari, G.R. (eds) Advances in Artificial Intelligence – IBERAMIA 2010. IBERAMIA 2010. Lecture Notes in Computer Science(), vol 6433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16952-6_56
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DOI: https://doi.org/10.1007/978-3-642-16952-6_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16951-9
Online ISBN: 978-3-642-16952-6
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