Abstract
Autonomous robots can use a variety of sensors, such as sonar, laser range finders, and bump sensors, to sense their environments. Visual information from an onboard camera can provide particularly rich sensor data. However, processing all the pixels in every image, even with simple operations, can be computationally taxing for robots equipped with cameras of reasonable resolution and frame rate. This paper presents a novel method for a legged robot equipped with a camera to use selective visual attention to efficiently recognize objects in its environment. The resulting attention-based approach is fully implemented and validated on an Aibo ERS-7. It effectively processes incoming images 50 times faster than a baseline approach, with no significant difference in the efficacy of its object detection.
Chapter PDF
References
Yarbus, A.L.: Eye movements during perception of complex objects. In: Riggs, L.A. (ed.) Eye movements and vision, pp. 171–196. Plenum Press, New York (1967)
Sprague, N., Ballard, D., Robinson, A.: Modeling attention with embodied visual behaviors (2005), http://www.cs.rochester.edu/~dana/WalterTheory25.pdf
Mitsunaga, N., Asada, M.: Sensor space segmentation for visual attention control of a mobile robot based on information criterion. In: Proceedings of the IEEE International Conference on Intellegent Robots and Systems, IEEE Computer Society Press, Los Alamitos (2001)
Kwok, C., Fox, D.: Reinforcement learning for sensing strategies. In: Proceedings of the IEEE International Conference on Intelligent Robots and Systems, IEEE Computer Society Press, Los Alamitos (2004)
Najemnik, J., Geisler, W.: Optimal eye movement strategies in visual search. Nature 434, 387–391 (2005)
Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998)
Salah, A.A., Alpaydin, E., Akarun, L.: A selective attention-based method for visual pat- tern recognition with application to handwritten digit recognition and face recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(3) (March 2002)
Walther, D., Rutishauser, U., Koch, C., Perona, P.: On the usefulness of attention for object recognition. In: The 2nd Workshop on Attention and Performance in Computer Vision (2004)
Shi, J., Tomasi, C.: Good features to track. In: IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society Press, Los Alamitos (1994)
Baluja, S., Pomerleau, D.: Expectation-based selective attention for visual monitoring and control of a robot vehicle. Robotics and Autonomous Systems 22(3–4) (1997)
Dellaert, F., Fox, D., Burgard, W., Thrun, S.: Monte carlo localization for mobile robots. In: ICRA 1999. Proceedings of the IEEE International Conference on Robotics and Automation, IEEE Computer Society Press, Los Alamitos (1999)
Sridharan, M., Kuhlmann, G., Stone, P.: Practical vision-based monte carlo localization on a legged robot. In: IEEE International Conference on Robotics and Automation, April 2005, IEEE Computer Society Press, Los Alamitos (2005)
Schilling, R.: Fundamentals of Robotics: Analysis and Control. Prentice-Hall, Englewood Cliffs (2000)
Stone, P., Dresner, K., Fidelman, P., Jong, N.K., Kohl, N., Kuhlmann, G., Sridharan, M., Stronger, D.: The UT Austin Villa 2004 RoboCup four-legged team: Coming of age. The University of Texas at Austin, Department of Computer Sciences, AI Laboratory, Tech. Rep. UT-AI-TR-04-313 (October 2004)
Bunting, J., Chalup, S., Freeston, M., McMahan, W., Middleton, R., Murch, C., Quinlan, M., Seysener, C., Shanks, G.: Return of the NUbots! the 2003 NUbots team report (2003), http://robots.newcastle.edu.au/publications/NUbotFinalReport2003.pdf
Mitsunaga, N., Toichi, H., Izumi, T., Asada, M.: Babytigers 2003: Osaka legged robot team (2003), http://www.er.ams.eng.osaka-u.ac.jp/robocup/BabyTigers/BabyTigers-TechReport-2003.pdf
Roefer, T., et al.: German team: Robocup 2004 (2004), http://www.germanteam.org/GT2004.pdf
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Stronger, D., Stone, P. (2007). Selective Visual Attention for Object Detection on a Legged Robot. In: Lakemeyer, G., Sklar, E., Sorrenti, D.G., Takahashi, T. (eds) RoboCup 2006: Robot Soccer World Cup X. RoboCup 2006. Lecture Notes in Computer Science(), vol 4434. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74024-7_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-74024-7_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74023-0
Online ISBN: 978-3-540-74024-7
eBook Packages: Computer ScienceComputer Science (R0)