Affiliations: [a] Department of Electrical and Computer Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA
| [b] Department of Electrical and Computer Engineering, The University of Texas, San Antonio, TX, USA
Note: [1] This work is supported by the National Science Foundation under the award numbers 1832110 and 2000320 as well as Air Force Research Laboratory and Office of the Secretary of Defense under agreement number FA8750-15-2-0116.
Abstract: Fuzzy logic controllers can handle complex systems by incorporating expert’s knowledge in the absence of formal mathematical models. Further, fuzzy logic controllers can effectively capture and accommodate uncertainties that are inherent in real-world controlled systems. On the other hand, Robot Operating System (ROS) has been widely used for many robotic applications due to its modular structure and efficient message-passing mechanisms for the integration of system’s components. For this reason, Robot Operating System is an ideal tool for developing software stacks for robotic applications. This paper develops a generic and configurable Robot Operating System package for the implementation of fuzzy logic controllers, particularly type-1 and interval type-2, which are based on either Mamdani or Takagi-Sugeno-Kang fuzzy inference mechanisms. This is achieved by employing a systematic object-oriented approach using the Unified Model Language (UML) to implement the fuzzy inference system as a single class that is composed of fuzzifier, inference, and defuzzifier classes. The deployment of the developed Robot Operating System package is demonstrated by implementing an interval type-2 fuzzy logic control of an Unmanned Aerial Vehicle (UAV).
