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Dual-coding representations for robot vision programming in Tekkotsu

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Abstract

We describe complementary iconic and symbolic representations for parsing the visual world. The iconic pixmap representation is operated on by an extensible set of “visual routines” (Ullman, 1984; Forbus et al., 2001). A symbolic representation, in terms of lines, ellipses, blobs, etc., is extracted from the iconic encoding, manipulated algebraically, and re-rendered iconically. The two representations are therefore duals, and iconic operations can be freely intermixed with symbolic ones. The dual-coding approach offers robot programmers a versatile collection of primitives from which to construct application-specific vision software. We describe some sample applications implemented on the Sony AIBO.

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Authors and Affiliations

  1. Computer Science Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, 15213, USA

    David S. Touretzky

  2. Computation and Neural Systems Program, California Institute of Technology, California, USA

    Neil S. Halelamien

  3. Robotics Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, 15213, USA

    Ethan J. Tira-Thompson & Kei Usui

  4. P. O. Box 821650, Vancouver, WA, 98682, Canada

    Jordan J. Wales

Authors
  1. David S. Touretzky
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  2. Neil S. Halelamien
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  3. Ethan J. Tira-Thompson
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  4. Jordan J. Wales
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  5. Kei Usui
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Corresponding author

Correspondence to David S. Touretzky.

Additional information

David S. Touretzky is a Research Professor in the Computer Science Department and the Center for the Neural Basis of Cognition at Carnegie Mellon University. He earned his B.A. in Computer Science from Rutgers University in 1978, and his M.S. (1979) and Ph.D. (1984) in Computer Science from Carnegie Mellon. Dr. Touretzky’s research interests are in computational neuroscience, particularly representations of space in the rodent hippocampus and related structures, and high level primitives for robot programming. He is presently developing an undergraduate curriculum in cognitive robotics based on the Tekkotsu software framework described in this article.

Neil S. Halelamien earned a B.S. in Computer Science and a B.S. in Cognitive Science at Carnegie Mellon University in 2004, and is currently pursuing his Ph.D. in the Computation & Neural Systems program at the California Institute of Technology. His research interests are in studying vision from both a computational and biological perspective. He is currently using transcranial magnetic stimulation to study visual representations and information processing in visual cortex.

Ethan J. Tira-Thompson is a graduate student in the Robotics Institute at Carnegie Mellon University. He earned a B.S. in Computer Science and a B.S. in Human-Computer Interaction in 2002, and an M.S. in Robotics in 2004, at Carnegie Mellon. He is interested in a wide variety of computer science topics, including machine learning, computer vision, software architecture, and interface design. Ethan’s research has revolved around the creation of the Tekkotsu framework to enable the rapid development of robotics software and its use in education. He intends to specialize in mobile manipulation and motion planning for the completion of his degree.

Jordan J. Wales is completing a Master of Studies in Theology at the University of Notre Dame. He earned a B.S. in Engineering (Swarthmore College, 2001), an M.Sc. in Cognitive Science (Edinburgh, UK, 2002), and a Postgraduate Diploma in Theology (Oxford, UK, 2003). After a year as a graduate research assistant in Computer Science at Carnegie Mellon, he entered the master’s program in Theology at Notre Dame and is now applying to doctoral programs. His research focus in early and medieval Christianity is accompanied by an interest in medieval and modern philosophies of mind and their connections with modern cognitive science.

Kei Usui is a masters student in the Robotics Institute at Carnegie Mellon University. He earned his B.S. in Physics from Carnegie Mellon University in 2005. His research interests are reinforcement learning, legged locomotion, and cognitive science. He is presently working on algorithms for humanoid robots to maintain balance against unexpected external forces.

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Touretzky, D.S., Halelamien, N.S., Tira-Thompson, E.J. et al. Dual-coding representations for robot vision programming in Tekkotsu. Auton Robot 22, 425–435 (2007). https://doi.org/10.1007/s10514-007-9024-0

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  • DOI: https://doi.org/10.1007/s10514-007-9024-0

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