Abstract
Recently, view-based or appearance-based approaches have been attracting the interests of computer vision research. We have already proposed a visual view-based navigation method using a model of the route called the “View Sequence,” which contains a sequence of front views along a route memorized in the recording run. In this paper, we apply an omnidirectional vision sensor to our view-based navigation and propose an extended models of a route called the “Omni-View Sequence.” Matching of Omni-Views are achieved using template matching by hardware. The omnidirectional vision sensor is a desirable sensor for real-time view-based recognition of a mobile robot in that the all information around the robot can be acquired simultaneously. As the view-based recognition can be more stable if the view contains more information, the robot can realize more stable matching and more accurate navigation compared with our former navigation method using the View Sequence.
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References
H. Ishiguro, T. Miyashita, and S. Tsuji. T-Net for Navigating a Vision-Guided Robot in a Real World. In Proc. of IEEE Int. Conf. on Robotics and Automation, pages 1068–1073, 1995.
I. Horswill. Polly: A Vision-Based Artificial Agent. In Proc. of Int’l Conf. on AAAI ’93, pages 824–829, 1993.
H. Inoue, M. Inaba, T. Mori, and T. Tachikawa. Real-Time Robot Vision System based on Correlation Technology. In Proc. of Int’l Symp. on Industrial Robots (ISIR), pages 675–680, 1993.
J.Y. Zheng and S. Tsuji. Panoramic Representation for Route Recognition by Mobile Robot. International Journal of Computer Vision, 9(l):55–76, 1992.
Shree K.Nayar, Hiroshi Murase, and Sameer A.Nene. Learining, Positioning, and Tracking Visual Apperance. In Proc. of IEEE Int’l Conf. on Robotics and Automation, pages 3237–3244, 1996.
K. Yamazawa, Y. Yagi, and M. Yachida. Obstacle Detection with Omnidirectional Image Sensor Hyper Omni Vision. In Proc. of IEEE Int. Conf. on Robotics and Automation, pages 1062–1067, 1995.
Takeshi Maeda, Hiroshi Ishiguro, and Saburo Tusji. Memory-Based Navigation using Omni-Directional View in Unknown Environment. In The Information Processing Society Repot (In Japanese), volume 95–10, pages 73–80, 1995.
Sakashi Maeda, Yoshinori Kuno, and Yoshiaki Shirai. Active Navigation Vision Based on Eigenspace Analysis. In Proc. of Int’l Conf. on Intelligent Robots and Systems (IROS), pages 1018–1023, 1997.
Y. Matsumoto, M. Inaba, and H. Inoue. Visual Navigation using View-Sequenced Route Representation. In Proc. of IEEE Int. Conf. on Robotics and Automation, pages 83–88, 1996.
M.A. Turk and A.P. Pentland. Face Recognition Using Eigenfaces. In Proc. of IEEE Conf. on Computer Vision and Pattern Recognition, pages 586–591, 1991.
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© 1998 Springer-Verlag London Limited
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Matsumoto, Y., Inaba, M., Inoue, H. (1998). Memory-Based Navigation using Omni-View Sequence. In: Zelinsky, A. (eds) Field and Service Robotics. Springer, London. https://doi.org/10.1007/978-1-4471-1273-0_28
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DOI: https://doi.org/10.1007/978-1-4471-1273-0_28
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1275-4
Online ISBN: 978-1-4471-1273-0
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