An expert fuzzy cognitive map for reactive navigation of mobile robots

Motlagh, Omid; Tang, Sai Hong; Ismail, Nafeeza Mohd; Ramli, Abdul Rahman

doi:10.1016/j.fss.2011.12.013

Cited by 62 publications

(24 citation statements)

References 29 publications

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“…They designed each behavior as a different fuzzy system while the outputs of all the systems were integrated for the robot's motion. Motlagh et al [26] used fuzzy cognitive maps to enable the system learn the required fuzzy rules. Kala et al [27] embedded neurons in the workspace in a 2-layer hierarchy for processing of information giving a near-real time trajectory.…”

Section: Related Researchmentioning

confidence: 99%

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Kala

Warwick

2015

Electronics

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Autonomous vehicles operate in real time traffic scenarios and aim to reach their destination from their source in the most efficient manner possible. Research in mobile robotics provides a variety of sophisticated means with which to plan the path of these vehicles. Conversely professional human drivers usually drive using instinctive means, which enables them to reach their goal almost optimally whilst still obeying all traffic laws. In this paper we propose the use of fuzzy logic for novel motion planning. The planner is generated using an evolutionary algorithm which resembles the learning stage of professional drivers. Whether to overtake or not, is a decision which affects one's driving and the decision is made using some deliberation. We further extend the approach to perform decision making regarding overtaking for all vehicles. Further we coordinate the motion of the vehicles at a traffic crossing to avoid any potential jam or collision. Experimental results prove that by using this approach we have been able to make the vehicles move in an optimal manner in a variety of scenarios.

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Section: Related Researchmentioning

confidence: 99%

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Kala

Warwick

2015

Electronics

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“…For this approach appropriate sensors, suitable analysis routines as well as fast computational processing are needed to realize on-the-go execution. In order to improve the tracking control performance, various soft computing methods as neural networks [20], fuzzy logic [19], and evolutionary algorithms [16] have also been applied to reactive control systems.…”

Section: Autonomous Platformsmentioning

confidence: 99%

Robots for Field Operations with Comprehensive Multilayer Control

2013

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Today research within agricultural technology focuses beside productivity and operation costs mainly on increasing the resource efficiency of crop production. Autonomous machines have the potential to significantly contribute to this by utilizing more multi-factorial real-time sensing and embedding artificial intelligence. A multilayer controller has successfully been implemented on two outdoor machines with various implements to conduct several agricultural applications in autonomous mode. Future work has to be conducted to achieve a more integrated and flexible implement control.

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“…One possible reason for the lack of reported investigation into goal-oriented FCM analysis is the difficulty in reversing the matrix multiplication and non-linear transformations involved in computing successive FCM states [4]. As mentioned in [5], there is a vast interest in FCMs and this interest on the part of researchers and industry is increasing, especially in the areas of control [4], [6], [7], business [8], [9], medicine [10]- [12], robotics [13], emotion modeling [14], environmental science [15], [16], education [17], information technology [16] and self-tuning controller design [19].…”

Section: Introductionmentioning

confidence: 99%

Triangular fuzzy number representation of relations in Fuzzy Cognitive Maps

Yeşil

Dodurka

Urbas

2014

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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In this paper, the conventional Fuzzy Cognitive Maps (FCMs), which has already achieved success in many fields, are extended by using triangular fuzzy numbers (TFNs). The advantage of FCMs is that they are relatively easy to construct and parameterize and are capable of handling the full range of system feedback structure, including density-dependent effects. However, it is a well-known fact that there are some limitations inherent in FCM, such as lack of adequate capability to handle uncertain information and lack of enough ability to aggregate the information from different sources. Triangular fuzzy numbers which are represented by a triplet has the capacity to represent the uncertain relations between the concepts. In this context, the weight matrix representing the causal relations are enhanced to a fuzzy weight matrix that has TFNs as element. As a result of this improvement, the dynamic reasoning algorithm of the conventional FCM is improved for the use of the proposed novel FCM. The proposed FCM is presented via four simulations and the results are discussed. The results of the simulation study shows how easily the uncertain information can be represented and interpreted by the proposed FCM design methodology.

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An expert fuzzy cognitive map for reactive navigation of mobile robots

Cited by 62 publications

References 29 publications

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Robots for Field Operations with Comprehensive Multilayer Control

Triangular fuzzy number representation of relations in Fuzzy Cognitive Maps

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