Abstract
The application of fuzzy techniques in robotics has become widespread in the last years and in different fields of robotics, such as behavior design, coordination of behavior, perception, localization, etc. The significance of the contributions was high until the end of the 1990s, where the main aim in robotics was the implementation of basic behaviors. In the last years, the focus in robotics moved to building robots that operate autonomously in real environments; the actual impact of fuzzy techniques in the robotics community is not as deep as it was in the early stages of robotics or as it is in other application areas (e. g., medicine, processes industry …). In spite of this, new emerging areas in robotics such as human–robot interaction, or well-established ones, such as perception, are good examples of new potential realms of applications where (hybridized) fuzzy approaches will surely be capable of exhibiting their capacity to deal with such complex and dynamic scenarios.
Keywords
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- CORE:
-
Computing Research and Education
- DOF:
-
degree of freedom
- DSP:
-
digital signal processor
- ERA:
-
Excellence in Research for Australia
- FLC:
-
fuzzy logic controller
- FLS:
-
fuzzy logic system
- GFS:
-
genetic fuzzy system
- LQR:
-
linear-quadratic regulator
- PID:
-
proportional-integral-derivative
- RFID:
-
radio frequency identification
- SLAM:
-
simultaneous localization and mapping
- TSK:
-
Takagi–Sugeno–Kang
- UAV:
-
unmanned aerial vehicle
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Rodríguez Fdez, I., Mucientes, M., Bugarín Diz, A. (2015). Application of Fuzzy Techniques to Autonomous Robots. In: Kacprzyk, J., Pedrycz, W. (eds) Springer Handbook of Computational Intelligence. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43505-2_20
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