Ruspini, E.H., A. Saffioti, K. Konolige. "Progress in Research on Autonomous Vehicle Motion Planning." Industrial Applications of Fuzzy Logic and Intelligent Systems. Edited by J. Yen, R. Langari and L. A. Zadeh, IEEE Press, 1995. Home/Search Document Details and Download
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Fuzzy Tracking Methods for Mobile Robots - Ollero, al. (4 citations) (Correct)
.... not suffice to meet the needs of real world tasks, hybrid solutions have been devised that blend low level reactive behaviours with a high level plan, used to supervise overall mission execution by activating and deactivating behaviours either sequentially [10] or by means of fuzzy transitions [11]. But the obtention of actor data (command reference values) from sensor data (observation variables) for autonomous mobile robot navigation is a complex task. One interesting approach aiming to reduce complexity and to add flexibility is to deal with a fuzzy system that encapsulates sets of rules ....
Ruspini, E.H., A. Saffioti, K. Konolige. "Progress in Research on Autonomous Vehicle Motion Planning." Industrial Applications of Fuzzy Logic and Intelligent Systems. Edited by J. Yen, R. Langari and L. A. Zadeh, IEEE Press, 1995.
A Fuzzy Logic Based Extension to Payton and Rosenblatt's Command.. - Yen (1995) (27 citations) (Correct)
....researchers have also applied fuzzy logic to mobile robot navigation with different focus. Ruspini and his colleagues have developed a fuzzy logic based approach to the explicit representation and execution of complex navigation plan, which was implemented in SRI s award winning robot Flaky [12]. The use of VLSI fuzzy inferencing chips for implementing sensor based fuzzy behaviors has also been demonstrated by Pin and Watanabe [13] D. Relationship between Payton Rosenblatt Approach and Fuzzy Logic Even though Payton and Rosenblatt s (P R) method was not presented as a fuzzy logic ....
E. Ruspini, A. Saffiotti, and K. Konolige, Progress in Research on Autonomous Vehicle Motion Planning, chapter 8, IEEE Press, 1994.
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