Áron Ballagi

Signatures: Definitions, operators and applications to fuzzy modelling

This paper presents a new framework for the symbolic representation of data which is referred to as signatures. The definitions of signatures and of signature trees are first given. Original operators on signatures are next presented, i.e., contraction, extension, pruning, addition, multiplication, and grafting. Attractive applications of signatures related to the modelling of fuzzy inference systems are suggested and discussed. An example is included to accompany the theoretical results.

Decision making in multi-robot cooperation by fuzzy signature sets

This paper presents some examples for fuzzy communication and intention guessing from the real life to the cooperation of intelligent mobile robots. In a special experimental environment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems.

Fuzzy communication and cooperation of mobile robots

Intelligent cooperation of agents/entities in autonomous robotics is a new and very exiting research field. If one plans/implements a cooperating robot system with intelligent behavior, not all scenarios appearing in the “life of robots” can be programmed in advance and thus effective, fast and compact communication is one of the most important cornerstones of the high-end cooperating system. Communication itself is very expensive so, generally speaking, it is much more advisable to build up as big as possible contextual knowledge bases and codebooks in distant on-board robot controller computers in order to shorten the communication process if it essentially reduces the amount of information that must be transmitted from one to another, than to concentrate all contextual knowledge in one of them and then to export its respective parts whenever they are needed in the other(s). It seems to be very important in the cooperation and communication of intelligent robots or physical agents that the information exchange among them is as effective and compressed as possible.

Fuzzy Signature Based Fuzzy Communication of Mobile Robots

This paper presents a novel method for control cooperating robots where the explicit communication line is substituted with fuzzy communication algorithms. Fuzzy signatures are used in a context dependent codebook, as complex state description method for intention guessing and action selection. Finally a possible cooperative robot application on a realistic example with missing data components will be shown.

Fuzzy Communication and Motion Control by Fuzzy Signatures in Intelligent Mobile Robots

This paper presents two examples for the deployment of fuzzy signatures in the field of intelligent mobile robots. The first shows a complex lateral drift control method base on fuzzy signatures. This method considers the motion system of the robot as a whole, unlike as simple parts of a complex system. The state space is written down by fuzzy signatures which add up flexibility, adaptability and learning ability to the system. In the second experiment a new communication approach is investigated for intelligent cooperation of autonomous mobile robots. Effective, fast and compact communication is one of the most important cornerstones of a high-end cooperating system. In this paper we propose a fuzzy communication system where the codebooks are built up by fuzzy signatures. We use cooperating autonomous mobile robots to solve some logistic problems.

Fuzzy signature based description of complex overtaking and engagement conflicts in railway traffic control

The railway traffic system and its respective subsystems, especially station and timetable management are extremely large and complex systems comprising a multitude of complex structured data. The theoretical and pre-planned traffic control is calculating with idealized traffic situations, but the real life scenes often suffer from conflicts and deviations. The complex traffic conflict states include uncertain conditions and vagueness of information. Classical methods cannot work properly under these uncertain conditions. In this paper we propose a new approach to describe these complex conflict situations using fuzzy signatures for recognizing and describing traffic conflicts in a hierarchically structured manner.

A new fuzzy graph and signature based approach to describe fuzzy situational maps

Computational tasks involving intelligent agents often need to process complex structured information. The way of describing this information greatly influences the performance of the agent. Therefore, a big issue is how the complex data describing that valuable information is not lose while it can also be processed in tractable time. Fuzzy signatures and their multidimensional geometric extension, fuzzy situational maps, are used to describe such complex structured data. These problems are examined in the context of a cooperative mobile robot task and a new method is developed for the simplified describing and processing of the complex inner relations in fuzzy situational maps. This paper mainly deals with the fundamentals of this method.

Intelligent Robot Cooperation with Fuzzy Communication

Designing the decision-making engine of a robot which works in a collaborative team is a challenging task. This is not only due to the complexity of the environment uncertainty, dynamism and imprecision, but also because of the coordination of the team has to be included in this design. The robots must be aware of other robots’ actions in order to cooperate and to successfully achieve their common goal. In addition, decisions must be made in real-time and using limited computational resources. In this chapter we propose some novel algorithms for action selection in ambiguous tasks where the communication opportunities among the robots are very limited.

Fuzzy Situational Maps: A new approach in mobile robot cooperation

Intelligent robot cooperation tasks have very complex decision-making and computational processes. Collecting and calculating with a high amount of data is one of the weakest point of such system. In addition all of these it is necessary to process in real-time with limited computational capacity. In this paper we propose some novel algorithms for coping with these problems and give some information about the Fuzzy Situational Maps as a special case of the Fuzzy Signatures. An example takes to the field of warehouse logistics, managing and arranging boxes will be presented.

Robot path planning map pre-optimization by Multilayer Fuzzy Situational Maps

S t r e s z c z e n i e Zadania inteligentnego planowania ruchu robota obejmują bardzo złożone procesy decyzyjne oraz obliczeniowe. Agregacja i przetwarzanie dużej ilości danych są jednym z najsłabszych punktów tego typu systemów. Dodatkowo, przetwarzanie konieczne jest w czasie rzeczywistym przy ograniczonej mocy obliczeniowej. W artykule zaproponowano kilka nowych algorytmów, które radzą sobie z tymi problemami oraz przedstawiono informacje na temat rozmytych map sytuacyjnych oraz wielowarstwowych rozmytych map sytuacyjnych jako wielowymiarowego rozwinięcia rozmytych sygnatur. Przedstawiony przykład dotyczy metody wstępnej optymalizacji planowania ruchu robota z użyciem rozmytych map sytuacyjnych. Słowa kluczowe: rozmyte mapy sytuacyjne, roboty mobilne