Abstract
This paper presents the design, implementation and evaluation of a trainable vision guided mobile robot. The robot, CORGI, has a CCD camera as its only sensor which it is trained to use for a variety of tasks. The techniques used for train ing and the choice of natural light vision as the primary sensor makes the methodology immediately applicable to tasks such as trash collection or fruit picking. For example, the robot is readily trained to perform a ball finding task which involves avoiding obstacles and aligning with tennis balls. The robot is able to move at speeds up to 0.8 ms-1 while performing this task, and has never had a collision in the trained environment. It can process video and update the actuators at 11 Hz using a single $20 microprocessor to perform all computation. Further results are shown to evaluate the system for generalization across unseen domains, fault tolerance and dynamic environments.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Braitenberg, V. (1984). Vehicles: Experiments in Synthetic Psychology, MIT Press, Cambridge, MA.
Carpenter, G.A. & Grossberg, S. (1987) A Massively Parallel Architecture for a Self-Organising Neural Pattern Recogntion Machine. Computer Vision, Graphics, and Image Processing, vol. 37, pp. 54–115.
Cheeseman, M. (1988) Build a Braitenberg Vehicle! Electronics Australia, vol. 50, no. 3, pp. 60–64.
Connell, J.H. (1990) Minimalist Mobile Robotics: a colony-style arhitecture for an artificial creature, Academic Press Inc.
Dewdney A.K. (1987) Braitenberg memoirs: vehicles for probing behavior roam a drak plain marked with lights. Scientific American, vol. 256, no. 3, March 1987.
Donnart, J-Y & Meyer, J-A (1996) Learning Reactive and Planning Rules in a Motivationally Autonomous Animat. IEEE Transactions on Systems, Man and Cybernetics, vol. 26, no. 3, June 1996, pp. 381–395.
Dorigo, M. & Colombetti, M. (1995) Robot Shaping: Developing autonomous agents through learning. Artificial Intelligence, vol. 71, no. 2, pp. 321–370.
Eccles, M. (ed.) (1997) New video camera has $8 price tag. Electronics World, vol. 104, no. 1739, December 1997, pp. 973.
Floreano, D. & Mondada, F. (1996) Evolution of Homing Navigation in a Real Mobile Robot. IEEE Transactions on Systems, Man and Cybernetics, vol. 26, no. 3, June 1996.
Harvey, I., Husbands, P. & Cliff, D. (1994) Seeing the Light: Artificial Evolution, Real Vision, From Animals to Animats: Proceedings of the Third International Conference on Simulation of Adaptive behavior, The MIT Press.
Hertz, J.A., Palmer, R.G. & Krogh A.S. (1991). Introduction to the theory of neural computation, Addison-Wesley.
Hitachi (1996), SH7604 Hardware User Manual, Available at http://www.halsp.hitachi.com, Hitachi Web Site.
Mahadevan, S. & Connell, J. (1991) Automatic programming of behavior-based robots using reinforcement learning. Artificial Intelligence, vol. 55, Elsevier, pp. 311–365.
Meeden, L.A. (1996) An Incremental Approach to Developing Intelligent Neural Network Controllers for Robots. IEEE Transactions on Systems, Man and Cybernetics, vol. 26, no. 3.
Meng, M., & Kak, A.C. (1993) Mobile Robot Navigation Using Neural Networks and Nonmetrical Environment Models, IEEE Control Systems, October 1993, pp. 30–39.
Millan, J.delR. (1995) Reinforcement learning of goal-directed obstacle-avoidance strategies in an autonomous mobile robot. Robotics and Autonomous Systems, vol. 15, no. 3, 1995.
Nehmzow, U. (1995) Flexible control of mobile robots through autonomous competence acquisition. Measurement and Control, vol. 28, pp. 48–54.
Pomerleau, D.A. (1993) Neural Network Perception for Mobile Robot Guidance, Kluwer Academic Publishers.
Rosenblatt, F. (1962) Principles of Neurodynamics, Spartan.
Sonka, M. (1993) Image processing, analysis and machine vision. London, Chapman and Hall Computing.
Widrow, B., & Hoff, M.E. (1960) Adaptive Switching Circuits. 1960 IRE WESCON Convention Record, part 4, pp. 96–104.
Wyeth, G. F. (1997), Active Vision for Embedded Systems, Proc. Mechatronics and Machine Vision in Practice, Toowoomba, Australia, IEEE Computer Society Press, September 1997, pp. 240–245.
Rights and permissions
About this article
Cite this article
Wyeth, G. Training a Vision Guided Mobile Robot. Machine Learning 31, 201–222 (1998). https://doi.org/10.1023/A:1007405111315
Issue Date:
DOI: https://doi.org/10.1023/A:1007405111315