Abstract
The way of understanding the role of perception along the intelligent robotic systems has evolved greatly since classic approaches to the reactive behavior-based approaches. Classic approaches tried to model the environment using a high level of accuracy while in reactive systems usually the perception is related to the actions that the robot needs to undertake so that such complex models are not generally necessary. Regarding hybrid approaches is likewise important to understand the role that has been assigned to the perception in order to assure the success of the system. In this work a new perceptual model based on fuzzy logic is proposed to be used in a hybrid deliberative-reactive architecture. This perceptual model deals with the uncertainty and vagueness underlying to the ultrasound sensor data, it is useful to carry out the data fusion from different sensors and it allows us to establish various levels of interpretation in the sensor data. Furthermore, using this perceptual model an approximate world model can be built so that the robot can plan its motions for navigating in an office-like environment. Then the navigation is accomplished using the hybrid deliberative-reactive architecture and taking into account the perceptual model to represent the robot's beliefs about the world. Experiments in simulation and in an real office-like environment are shown for validating the perceptual model integrated into the navigation architecture.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
J. Latombe, Robot Motion Planning, Kluver Academic Publishers, 1991.
R. Brooks, “A robust layered control system for a mobile robot,” IEEE Journal of Robotics andAutomation, vol. RA-2, pp. 14–23, 1986.
R. Arkin, “Path planning for a vision-based autonomous robot,” in Proc. of the SPIE Conference on Mobile Robots, 1986, pp. 240–249.
E. Gat, “Reliable goal-directed reactive control of autonomous mobile robots,” Ph.D. Thesis, Virginia Polytechnic Institute, 1991.
A. Saffiotti, K. Konolige, and E. Ruspini, “A multivalued logic approach to integrating planning and control,” Artificial Intelligence, vol. 76, pp. 481–526, 1995.
H. Hexmoor, D. Kortenkamp, R. Arkin, P. Bonasso, and D. Musliner, Lessons Learned from Implemented Software Architectures for Physical Agents, AAAI Spring Symposium Series, 1995.
R. Arkin, “Motor schema based navigation for a mobile robot,” in Proc. of the IEEE Int. Conf. on Robotics and Automation, 1987, pp. 264–271.
R. Arkin, “Integrating behavioral, perceptual and world knwledge in reactive navigation,” Robotics and Autonomous Systems, vol. 6, pp. 105–122, 1990.
E. Gat and G. Dorais, “Robot navigation by conditional sequencing,” in Proc. of the IEEE Int. Conf. on Robotics and Automation, 1994, pp. 1293–1299.
L. Zadeh, “The concept of linguistic variable and its applications to approximate reasoning,” Part I Information Sciences, vol. 8, pp. 199–249; Part II Information Sciences, vol. 8, pp. 301–357; Part III Information Sciences, vol. 9, pp. 43–80, 1975.
A. Bonarini and F. Basso, “Learning to compose fuzzy behaviors for autonomous agents,” International Journal on Approximate Reasoning, vol. 17, no.4, pp. 409–432, 1997.
S. Goodridge, M. Kay, and R. Luo, “Multi-layered fuzzy behavior fusion for reactive control of an autonomous mobile robot,” in Proc. IEEE Int. Conf. on Fuzzy Systems, Barcelona, Spain, 1997, pp. 579–584.
W. Li, “Fuzzy-logic based reactive behaviour control of an autonomuous mobile system in unknown environments,” Engineering Applications of Artificial Intelligence, vol. 7, no.5, pp. 521–531, 1994.
F. Michaud, “Selecting behaviors using fuzzy logic,” in Proc. IEEE Int. Conf. on Fuzzy Systems, Barcelona, Spain, 1997, pp. 585–592.
M. Sugeno and M. Nishida, “Fuzzy control of model car,” Fuzzy Sets and Systems, vol. 16, pp. 103–113, 1985.
T. Takeuchi, Y. Nagai, and N. Enomoto, “Fuzzy control of a mobile robot for obstacle avoidance,” Information Sciences, vol. 43, pp. 231–248, 1988.
A. Saffiotti, E. Ruspini, and K. Konolige, “Blending reactivity and goal-directedness in a fuzzy controller,” in Proc. of the IEEE Int. Conf. on Fuzzy Systems, San Francisco, California, 1993, pp. 134–139.
S. Goodridge and R. Luo, “Fuzzy behavior fusion for reactive control of an autonomous mobile robot: MARGE,” in Proc. of the IEEE Int. Conf. on Robotics and Automation, San Diego, CA, 1994, pp. 1622–1627.
W. Kim, J. Ko, and M. Chung, “Uncertain robot environment modeling using fuzzy numbers,” Fuzzy Sets and Systems, vol. 61, pp. 53–62, 1994.
J. Gasós and A. Martín, “A fuzzy approach to build sonar maps for mobile robots,” Computers in Industry, vol. 32, pp. 151–167, 1996.
H. Moravec and A. Elfes, “High resolution maps from wide angle sonar,” in Proc. IEEE Int. Conf. on Robotics and Automation, 1985, pp. 116–121.
G. Oriolo, G. Ulivi, and M. Vendittelli, “Real-time map building and navigation for autonomous robots in unknown environments,” IEEE Transactions on Systems, Man and Cybernetics. Part B: Cybernetics, vol. 28, no.3, pp. 316–333, 1998.
R. Arkin, Behavior-Based Robotics, The MIT Press, 1998.
E. Aguirre and A. González, “Integrating fuzzy topological maps and fuzzy geometric maps for behavioral-based robots,” International Journal of Intelligent Systems, vol. 17, no.3, pp. 333–368, 2002.
R. Bauer and W. Rencken, “Sonar feature based exploration,” in Proc. of the IEEE/RSI Int. Conf. on Intelligent Robots and Systems, 1995, pp. 148–153.
J. Crowley and P. Reignier, “World modeling and position estimation for a mobile robot using ultrasonic ranging,” in Proc. of the IEEE Int. Conf. on Robotics and Automation, 1989, pp. 674–680.
W. Rencken, “Concurrent localization and map building for mobile robots using ultrasonic sensors,” in Proc. of the IEEE/RSI Int. Conf. on Intelligent Robotics and Systems, 1993, pp. 2192–2197.
E. Aguirre, M. García-Alegre, and A. González, “A fuzzy safe follow wall behavior fusing simpler fuzzy behaviors,” in Proc. of the Third IFAC Symposium on Intelligent Autonomous Vehicles, Madrid, Spain, 1998, pp. 607–612.
E. Aguirre and A. González, “Fuzzy behaviors for mobile robot navigation: Design, coordination and fusion,” International Journal of Approximate Reasoning, vol. 25, pp. 255–289, 2000.
E. Aguirre, “A behavior-based architecture for mobile robot navigation,” Ph.D. Thesis, Department of Computer Science and Artificial Intelligence, Granada, Spain, 2000. (In spanish).
M. Mataric, “Integration of representation into goal-driven behavior-based robots,” IEEE Transactions on Robotics and Automation, vol. 8, no.3, pp. 304–312, 1992.
N. Technologies, “User's manual,” 1995.
L. Zadeh, “Fuzzy sets as a basis for a theory of possibility,” Fuzzy Sets and Systems, vol. 1, pp. 3–28, 1978.
D. Driankov, H. Hellerdoorn, and M. Reinfrank, An Introduction to Fuzzy Control, Kluwer Academic Publishers, 1993.
R. Yager and D.P. Filev, Essentials of Fuzzy Modeling and Control, John Wiley & Sons, Inc., 1994.
S. Thrun, “Learning metric-topological maps for indoor mobile robot navigation,” Artificial Intelligence, vol. 99, no.1, pp. 21–71, 1998.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Aguirre, E., González, A. A Fuzzy Perceptual Model for Ultrasound Sensors Applied to Intelligent Navigation of Mobile Robots. Applied Intelligence 19, 171–187 (2003). https://doi.org/10.1023/A:1026057906312
Issue Date:
DOI: https://doi.org/10.1023/A:1026057906312