A distributed robotic control system based on a temporal self-organizing neural network

Barreto, Guilherme A.; Araújo, A.F.R.; Dücker, Christof; Ritter, Helge

doi:10.1109/tsmcc.2002.806067

Cited by 13 publications

(4 citation statements)

References 36 publications

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“…Besides, they had been used in deep ocean detection [ 6 ] and telescope development [ 7 ]. Barreto et al proposed a robot control system using competitive and temporal Hebbian (CTH) network, which applies temporal self-organizing neural network [ 8 ]. By utilizing two sets of individual states, the individual states of the trajectory, and the temporal order of trajectory states, this network can utilize two sets of synaptic weights.…”

Section: A Survey On Robotic Control Applications Using Noninvasive M...mentioning

confidence: 99%

Noninvasive Human-Computer Interface Methods and Applications for Robotic Control: Past, Current, and Future

Liu

Zhang

et al. 2022

Computational Intelligence and Neuroscience

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The purpose of this study is to explore the noninvasive human-computer interaction methods that have been widely used in various fields, especially in the field of robot control. To have a deep understanding of the development of the methods, this paper employs “Mapping Knowledge Domains” (MKDs) to find research hotspots in the area to show the future potential development. Through the literature review, this paper found that there was a paradigm shift in the research of noninvasive BCI technologies for robotic control, which has occurred from early 2010 since the rapid development of machine learning, deep learning, and sensory technologies. This study further provides a trend analysis that the combination of data-driven methods with optimized algorithms and human-sensory-driven methods will be the key areas for the future noninvasive method development in robotic control. Based on the above findings, the paper provides a potential developing way of noninvasive HCI methods for related areas including health care, robotic system, and media.

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Section: A Survey On Robotic Control Applications Using Noninvasive M...mentioning

confidence: 99%

Noninvasive Human-Computer Interface Methods and Applications for Robotic Control: Past, Current, and Future

Liu

Zhang

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

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“…Yapay sinir ağlarını modellemek için denetimli veya denetimsiz öğrenme algoritmaları kullanılmaktadır. Mevcut çeşitli sinir ağı mimarileri ve öğrenme algoritmaları arasında, Kohonen'in self organizing map (SOM) (Banfield and Raftery 1992;Barreto et al 2002;Eter and As 2002), en önemli sinir ağı modellerinden biridir. Bu model, denetimsiz öğrenme algoritmasına sahip, retina -korteks haritalaması ile motive edilen ilişkisel bellek modeli için geliştirilmiştir.…”

Section: Yapay Zeka (Artificial Intelligence)unclassified

Nano Sistemlerde Hücreler Arası Haberleşmenin Analiz Edilmesi

Işik¹,

Tağluk²,

Işık³

2021

Journal of Intelligent Systems: Theory and Applications

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ÖzFarklı canlı türleri farklı zeka seviyelerine sahip olduğundan, akıl ve zekanın beyinle bir bağlantısının olabileceği düşünülmektedir. Akıl, bilinç ve zaka insanlık tarihinden beri bilim insanlarını etkileyen en etkileyici kavramlar arasında olmuştur. Ancak bilinci, yalnızca sinir sisteminin veya beynin bir ürünü olarak görmenin de uygun olmayacağı düşünülmektedir. Beynin, yaratıcılık, düşünce ve duygu vs. gibi organizasyonlardan sorumlu olduğu bilinmektedir. Bilincin varlığı için ise sinir sistemi veya beynin gerekli olmadığı birçok çalışma tarafından daha önce ispatlanmıştır. Bunun en basit örneği bitkilerin herhangi bir sinir sistemi veya beyni olmamasına rağmen güneşe yönelebilme bilinçlerinin olmasıdır. Bilinçli bir nano haberleşme modelin tasarlanabilmesi için öncelikle biyolojik canlıların ürettiği sinyallerin tasarlanan bu model ile elde edilmesi gerektiği düşünülmektedir. Çünkü canlıların bütün hücrelerinin bu sinyaller (aksiyon potansiyel) aracılığı ile birbiri arasında iletişim kurduklarına inanılmaktadır. Bu sebeple bu çalışma kapsamında, biyolojik hücrelerin ürettiği aksiyon potansiyel sinyaline neredeyse birebir benzer sinyal üreten elektronik bir devre tasarlanmıştır. Üretilen aksiyon potansiyelin gerçek bir nöron hücresinin ürettiği aksiyon potansiyele yakın olabilmesi için literatürdeki elektronik modellerde kullanılan elemanlar incelendikten sonra böyle bir sistem geliştirilmiş ve bu sistemde kullanılan parametrelerin değeri de yine üretilen aksiyon potansiyelin benzerliğini arttıracak şekilde uzun süren denemeler sonunda hassas bir şekilde tespit edilmiştir. Daha sonra ise tasarlanan model ile iki hücrenin birbiri ile haberleşmesinden elde edilen veriler incelenmiştir.

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“…For utilizing the processor resources, several tasks often run on a processor. The scheduling algorithms of this task not only affects the utilization of a processor but also controls the system's performance [6]. The optimum scheduling methodology opted for the multiprocessors is the NP hard, hence the heuristic algorithms are often adopted for the allocating tasks.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Based Resource Scheduling Technique for Distributed Robotic Control Systems

P¹,

Ramabalan²

2022

Computer Systems Science and Engineering

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The design of controllers for robots is a complex system that is to be dealt with several tasks in real time for enabling the robots to function independently. The distributed robotic control system can be used in real time for resolving various challenges such as localization, motion controlling, mapping, route planning, etc. The distributed robotic control system can manage different kinds of heterogenous devices. Designing a distributed robotic control system is a challenging process as it needs to operate effectually under different hardware configurations and varying computational requirements. For instance, scheduling of resources (such as communication channel, computation unit, robot chassis, or sensor input) to the various system components turns out to be an essential requirement for completing the tasks on time. Therefore, resource scheduling is necessary for ensuring effective execution. In this regard, this paper introduces a novel chaotic shell game optimization algorithm (CSGOA) for resource scheduling, known as the CSGOA-RS technique for the distributed robotic control system environment. The CSGOA technique is based on the integration of the chaotic maps concept to the SGO algorithm for enhancing the overall performance. The CSGOA-RS technique is designed for allocating the resources in such a way that the transfer time is minimized and the resource utilization is increased. The CSGOA-RS technique is applicable even for the unpredicted environment where the resources are to be allotted dynamically based on the early estimations. For validating the enhanced performance of the CSGOA-RS technique, a series of simulations have been carried out and the obtained results have been examined with respect to a selected set of measures. The resultant outcomes highlighted the promising performance of the CSGOA-RS technique over the other resource scheduling techniques.

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A distributed robotic control system based on a temporal self-organizing neural network

Cited by 13 publications

References 36 publications

Noninvasive Human-Computer Interface Methods and Applications for Robotic Control: Past, Current, and Future

Noninvasive Human-Computer Interface Methods and Applications for Robotic Control: Past, Current, and Future

Nano Sistemlerde Hücreler Arası Haberleşmenin Analiz Edilmesi

Metaheuristic Based Resource Scheduling Technique for Distributed Robotic Control Systems

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