Abstract
Interactive robotics demands real-time visual information about the environment. Real time vision processing, however, places a heavy load on the robot’s limited resources, and must accommodate other processes such as speech recognition, animated face displays, communication with other robots, navigation and control. For our entries in the 2000 American Association for Artificial Intelligence robot contest, we developed a vision module capable of providing real-time information about ten or more operators while maintaining at least a 20Hz frame rate and leaving sufficient processor time for the robot’s other capabilities. The vision module uses a probabilistic scheduling algorithm to ensure both timely information flow and a fast frame capture. The vision module makes its information available to other modules in the robot architecture through a shared memory structure. The information provided by the vision module includes the operator information along with a confidence measure and a time stamp. Because of this design, our robots are able to react in a timely manner to a wide variety of visual events.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
E. Bizzi, S. Giszter, E. Loeb, F.A. Mussa-Ivaldi, and P. Saltiel, “Modular organization of motor behavior in the frog’s spinal cord”, Trends in Neuroscience, 18:442–446.
R. P. Bonasso, R. J. Firby, E. Gat, D. Kortenkamp, D. P. Miller, and M. G. Slack, “Experiments with an architecture for intelligent, reactive agents”, J. of Experimental & Theoretical Artificial Intelligence, 9(2/3):237–256, 1997.
R. A. Brooks, “A robust layered control system for a mobile robot”, IEEE J. of Robotics and Automation, vol. 2,no. 1, 1986.
J. Bryson, “Cross-Paradigm Analysis of Autonomous Agent Architecture”, J. of Experimental and Theoretical Artificial Intelligence, vol. 12,no. 2, pp 165–190, 2000.
D. R. Forsey and R. H. Bartels, “Hierarchical B-spline refinement”, in Computer Graphics (SIGGRAPH’ 88), 22(4):205–212, August, 1988.
E. Gat, Reliable Goal-Directed Reactive Control of Autonomous Mobile Robots, Ph.D. thesis, Virginia Polytechnic Institute and State University, 1991.
IBM ViaVoiceTM Outloud API Reference Version 5.0, November 1999.
E. C. Ifeachor and B. W. Jervis, Digital Signal Processing. A Practical Approach, Addison Wesley Publishing Company, 1995.
D. Kortenkamp, R. P. Bonasso, and R. Murphy (ed.), Artificial Intelligence and Mobile Robots, AAAI Press/MIT Press, Cambridge, 1998.
B. A. Maxwell, L. A. Meeden, N. Addo, P. Dickson, N. Fairfield, N. Johnson, E. Jones, S. Kim, P. Malla, M. Murphy, B. Rutter, E. Silk, “REAPER: A Reflexive Architecture for Perceptive Agents”, AI Magazine, spring 2001.
B. A. Maxwell, L. A. Meeden, N. Addo, L. Brown, P. Dickson, J. Ng, S. Olshfski, E. Silk, and J. Wales, “Alfred: The Robot Waiter Who Remembers You,” in Proceedings of AAAI Workshop on Robotics, July, 1999. To appear in J. Autonomous Robots, 2001.
B. Maxwell, S. Anderson, D. Gomez-Ibanez, E. Gordon, B. Reese, M. Lafary, T. Thompson, M. Trosen, and A. Tomson, “Using Vision to Guide an Hors d’Oeuvres Serving Robot”, IEEE Workshop on Perception for Mobile Agents, June 1999.
H. P. Moravec, A. E. Elfes, “High Resolution Maps from Wide Angle Sonar”, Proceedings of IEEE Int’l Conf. on Robotics and Automation, March 1985, pp 116–21.
J. Neider, T. Davis, and M. Woo, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Addison-Wesley, Reading, MA, 1993.
F. I. Parke and K. Waters, Computer Facial Animation, A. K. Peters, Wellesley, MA, 1996.
A. Rosenfeld and J. L. Pfaltz, “Sequential operations in digital picture processing”, ACM, 13:471–494, October 1966.
D. Scharstein and A. Briggs, “Fast Recognition of Self-Similar Landmarks”, IEEE Workshop on Perception for Mobile Agents, June 1999.
H. Wu, Q. Chen, and M. Yachida, “Face Detection From Color Images Using a Fuzzy Pattern Matching Method”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21,no. 6, June 1999.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Maxwell, B.A., Fairfield, N., Johnson, N., Malla, P., Dickson, P., Kim, S. (2001). A Real-Time Vision Module for Interactive Perceptual Agents. In: Schiele, B., Sagerer, G. (eds) Computer Vision Systems. ICVS 2001. Lecture Notes in Computer Science, vol 2095. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48222-9_13
Download citation
DOI: https://doi.org/10.1007/3-540-48222-9_13
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42285-3
Online ISBN: 978-3-540-48222-2
eBook Packages: Springer Book Archive