{'fraction_non_alphanumeric': 0.013477088948787063, 'fraction_numerical': 0.0, 'mean_word_length': 5.2133891213389125, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Using fuzzy rule interpolation based automata for controlling navigation and collision avoidance behaviour of a robot

Relatively few Fuzzy Rule Interpolation (FRI) techniques can be found among the practical fuzzy rule based applications. Many of them have limitations from the direct application point of view, for example they can be applied only in one dimensional case, or defined based on the two closest surrounding rules of the actual observation. Additionally the FRI methods can dramatically simplify the building of fuzzy rule bases by enabling the application of sparse rule bases. FRI methods can provide reasonable (interpolated) conclusions even if none of the existing rules fires under the current observation. These methods can help the expert to concentrate on the cardinal actions only. Compared to the classical fuzzy CRI, by omitting the derivable rules, the number of the fuzzy rules needed to be handled during the design process could be dramatically reduced. This paper provides a brief overview of several FRI methods and in more detailed an application oriented simple and quick FRI method FIVE will be introduced. For the demonstration of the benefits of the interpolation-based fuzzy reasoning as systematic approach, a robot navigation application is presented, where the robot is able to cycle through waypoints while avoiding collision with obstacles and walls. All the controlling parts were accomplished with fuzzy rule bases of the FIVE FRI method.