Abstract
In this paper we present a complete control architecture for a mobile robot which enables it to achieve a set of proposed goals with a high degree of autonomy and to react to the changing environment in real time. Autonomy and robustness are achieved through careful selection and incremental implementation of a set of basic Motor-Behaviors that interpret the sensor readings (sonar, vision and odometric sensors) and actuate the motors. The plan is provided by a user, and is expressed as a sequence of goals and a series of hints on how to achieve them. These hints are based on the user's knowledge of the environment and of the robot's behavioral and perceptual abilities. A new set of behaviors, called Conductor-Behaviors, which inspect and modify Motor-Behaviors' attributes, have been introduced in order to link the robot's Motor-Behaviors to the user's plan. Finally, a canonical set of symbols, attached to the Motor-Behaviors, serves as well grounded symbols that the user can utilize to express the plans. We also report experimental results with a real robot that demonstrate how plans expressed as goals and hints to achieve them improve the robot's performance.
Similar content being viewed by others
References
Agre, P.E. and Chapman, D. 1990. What are plans for?. Robotics and Autonomous Systems, 6:17–34.
Aloimonos, J. 1990. Purposive and qualitative active vision, DARPA Image Understanding Workshop, pp. 816–828.
Arkin, R.C. 1989a. Integrating behavioral, perceptual and world knowledge in reactive navigation. In Designing Autonomous Agents, P. Maes (Ed.).
Arkin, R.C. 1989b. Towards the unification of navigational planning and reactive control, AAAI Spring Symposium on Robot Navigation, pp. 1–5.
Ballard, D.H. 1991. Animate vision. Artificial Intelligence, 48(1):57–86.
Bohrenstein, J. and Koren, Y. 1991. The vector field histogram-fast obstacle avoidance for mobile robots. IEEE Transactions on Robotics and Automation, 7(3):278–288.
Bonasso, R.P., Firby, R.J., Gat, E., Kortenkamp, D., Miller, D., and Slack, M. 1997. Experiences with an architecture for intelligent, reactive agents. Journal of Experimental and Theoretical Artificial Intelligence, 9(1):237–256.
Brooks, M.J., de Agapito, L., Huynh, D.Q., and Baumela, L. 1996. Direct methods for self-calibration of a moving stereo head. In Proc. ECCV'96, Cambridge, UK, Vol. 2, pp. 415–426.
Brooks, R.A. 1986. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automatition RA: 2(1):14–23.
Brooks, R.A. 1989. A robot that walks; emergent behavior from a carefully evolved network. Neural Computation, 1(2):253–262.
Brooks, R.A. 1990a. The behavior language; user's guide, A.I. Memo 1227, M.I.T.
Brooks, R.A. 1990b. Elephants don't play chess. Robotics and Autonomous Systems, 6:3–15.
Brooks, R.A. 1991. Intelligence without representation. Artificial Intelligence, 47:139–159.
Connell, J.H. 1989. A colony architecture for an artificial creature, M.I.T.A.I. Lab Tech Report 1151, M.I.T. Artificial Intelligence Laboratory.
Connell, J.H. 1991. SSS: A hybrid architecture applied to robot navigation, IEEE International Conference on Robotics and Automation, Nice, France, pp. 2719–2724.
Elfes, A. 1986. A distributed control architecture for an autonomous mobile robot. Artificial Intelligence, 1(2):135–144.
Faugeras, O. 1993. Three-dimensional Computer Vision: A Geometric Viewpoint, MIT Press.
Fikes, R.E. and Nilsson, N.J. 1971. STRIPS: A new approach to the application of theorem proving to problem solving. Artificial Intelligence, 2:189–208.
Firby, R.J. 1987. An investigation into reactive planning in complex domains. In Proc. Sixth National Conference on Artificial Intelligence, Seattle, pp. 202–206.
Flynn, A.M., Brooks, R.A., Wells, W.M., and Barret, D.S. 1989. The world's largest one cubic inch robot. In Proc. IEEE Micro Electro Mechanical Systems, IEEE, pp. 98–101.
Haigh, K. and Veloso, M. 1997. High-level planning and low level-level execution: Towards a complete robotic agent. In Proc. of the International Conference on Autonomous Agents (AA).
Haralick, R.M. and Shapiro, L.G. 1992. Computer and Robot Vision, Vol. 1, Addison Wesley: Reading, MA.
Harnard, S. 1995. Grounding symbolic capacity in robotic capacity. In The “Artificial Life” Route to “Artificial Intelligence”, L. Steels and R. Brooks (Eds.), Lawrence Erlbaum: New Haven, CT.
Hayes-Roth, B. 1993. Opportunistic control of action in intelligent agents. IEEE Transactions on Systems, Man, and Cybernetic, 23(6):1575–1587.
Horswill, I.D. 1992. Characterizing adaptation by constraint, Toward a practice of autonomous systems. In Proc. of the First European Conference on Artificial Life, MIT Press/Bradford Books, pp. 58–63.
Horswill, I.D. 1993. Specialitation of perceptual processes. Ph.D. thesis, MIT Artificial Intelligence Laboratory.
Horswill, I.D. 1995. Analysis of adaptation and environment, Artificial Intelligence, 73(1–2):1–30.
Horswill, I.D. and Brooks, R.A. 1988. Situated vision in a dynamic world: Chasing objects, AAAI-88, pp. 796–800.
Kaebling, L.P. and Rosenschein, S.J. 1990. Action and planning in embedded agents. Robotics and Autonomous Systems, 6:35–48.
Košecká, J., Bajcsy, R., and Mintz, M. 1994. Control of visually guided behaviors, GRASP Lab. Technical Report 367, Department of Computer and Information Science, University of Pennsylvania.
Lozano-Pérez, T. 1983. Spatial planning: A configuration space approach. IEEE Transactions on Computers, C-32(2):395–407.
Maes, P. 1989. How to do the right thing. Connection Science Journal, 1(3):291–323.
Malcolm, C. and Smithers, T. 1990. Symbol grounding via a hybrid architecture in an autonomous assembly system. Robotics and Autonomous Systems, 6:123–144.
Mataric, M.J. 1992. Integration of representation into goal-driven behavior-based robots. IEEE Transactions on Robotics and Automation, 8(3):304–312.
Moravec, H.P. 1977. Towards automatic visual obstacle avoidance. In Proc. of the 5th International Joint Conference on Artificial Intelligence (IJCAI), p. 584.
Moravec, H.P. 1988. Sensor fusion in certainty grids for mobile robots, AI Mag. pp. 61–74.
Myers, K.L. 1996. Advisable planning systems. In Advanced Planning Technology, A. Tate (Ed.), AAAI Press: Menlo Park, CA.
Noreils, F.R. and Chatila, R.G. 1995. Plan execution monitoring and control architecture for mobile robots. IEEE Journal of Robotics and Automatition, 11(2):255–266.
Parker, L.E. 1992. Adaptive action selection for cooperative agent teams. From Animals to Animats: International Conference on Simulation of Adaptive Behavior, pp. 442–450.
Payton, D.W. 1990. Internalized plans: A representation for action resources. Robotics and Autonomous Systems, 6:89–103.
Pfeifer, R. 1996. Symbols, patterns, and behavior: Towards a new understanding of intelligence. In Proc. Japanese Conference on Artificial Intelligence, Tokyo, pp. 1–15.
Saffiotti, A., Konolige, K., Myers, K., and Ruspini, E.H. 1997. The saphira architecture: A design for autonomy. Journal of Experimental and Theoretical Artificial Intelligence (JETAI). Special issue on Architecures for Physical Agents, 9(1):215–235.
Saffioti, A., Ruspini, E.H., and Konolige, K. 1993. A fuzzy controller for flakey, an autonomous mobile robot, Technical Note 529, Artificial Intelligence Center. SRI International, 333 Ravenswood Ave. Menlo Park, CA 94025, USA.
Schneider-Fontán, M. 1996. Planning based on active perception. Ph.D. Thesis, Universidad Complutense Madrid, Facultad CC. Fisicas.
Simmons, R. 1994. Structured control for autonomous robots. IEEE Transactions on Robotics and Automation, 10(1):34–43.
Simmons, R., Goodwin, R., Haigh, K., Koenig, S., and Sullivan, J. 1997. A layered architecture for office delivery robots. First International Conference on Autonomous Agents, Marina del Rey, CA, pp. 245–252.
Thomson, A.M. 1977. The navigation system of the JPL robot. In Proc. of the International Joint Conference on Artificial Inteligence, pp. 749–757.
Wilkins, D.E. and Myers, K.L. 1995. A common knowledge representation for plan generation and reactive execution. Journal of Logic and Computation, 5:731–761.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Schneider-Fontán, M. Plan Execution Based on Active Perception: Adding Hints to Plans. Autonomous Robots 6, 53–68 (1999). https://doi.org/10.1023/A:1008872509483
Issue Date:
DOI: https://doi.org/10.1023/A:1008872509483