Adaptable User Interface Based on the Ecological Interface Design Concept for Multiple Robots Operating Works with Uncertainty

Furukawa, Hiroshi

doi:10.3844/jcssp.2010.904.911

Cited by 8 publications

(7 citation statements)

References 18 publications

(20 reference statements)

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“…The first approach, used by Furukawa (2010), completely implemented again and improved, has enables us to judge to the effectiveness of that proposed. The scaling and comparisons done with rules discovered by ethologists at ants made it possible to show the consistency of found rules.…”

Section: Resultsmentioning

confidence: 99%

Optimization of Clustering Time by a Group of Autonomous Robots Making Use of an Exclusive Multi-Marking

Abdessemed¹

2010

Journal of Computer Science

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Problem statement: For solving complex issues, the current tendency goes towards the swarms behaviors, realized on a basis of collective interactions, which results from a cooperative work favoring exchanges between individuals of a same group at microscopic level and allowing the emergence of complex collective behaviors at macroscopic level. Many models were inspired by these attitudes to find simple rules, guiding mobile, autonomous robots with limited capacities in their environment in order to achieve tasks like those of exploration, self-assembly and gathering. Multimarking technique as indirect communication inside the same robots group can optimize time of such achievements Approach: A method based on the reversed emergence principle combined to a genetic algorithm is presented here, making evolve a global behavior inside simulated robots group called agent-robots, with an aim to find the micro-rules forming a heap according to two approaches. The first approach accomplishes an ordinary grouping and the second one, which we propose, based on the exclusive multi-marking principle. The control device, guiding these robots-agent to succeed this task, functions on a basis of sensor-motor rules being used to arbitrate between a given number of elementary behaviors with which we equip each one of them initially. Results: Simulation results, implemented according to a reactive agent's model, making it possible to show the consistency of the detected rules and the efficient of the proposed approach in comparison with the ordinary one, are provided and commented. The time optimization of grouping by robots like these can have a huge economic and strategic impact in sectors as important as industry, agriculture and military domain. Conclusion:Like examples, we can quote the grouping of goods in a warehouse, the grouping of ores from mines, the grouping of vegetables and fruits in gardens and the recovery of weapons, in real time, from a battle field. This work can be generalized, in the future, to the multi-heap formation to perform the classification task according to given criteria.

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Section: Resultsmentioning

confidence: 99%

Optimization of Clustering Time by a Group of Autonomous Robots Making Use of an Exclusive Multi-Marking

Abdessemed¹

2010

Journal of Computer Science

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“…The error signal e (n) is defined as the difference between the primary signal d (n) and the filter output y(n), that is Eq. 12 and 13, (Furukawa, 2010):…”

Section: Methodology Of Adaptive Filtermentioning

confidence: 99%

Comparative Evaluation of Adaptive Filter and Neuro-Fuzzy Filter in Artifacts Removal From Electroencephalogram Signal

Balaiah¹,

IlaVennila

2012

American Journal of Applied Sciences

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Problem statement:This study presents an effective method for removing mixed artifacts (EOG-Electro-ocular gram, ECG-Electrocardiogram, EMG-Electromyogram) from the EEGElectroencephalogram records. The noise sources increases the difficulty in analyzing the EEG and obtaining clinical information. EEG signals are multidimensional, non-stationary (i.e., statistical properties are not invariant in time), time domain biological signals, which are not reproducible. It is supposed to contain information about what is going on in the ensemble of excitatory pyramidal neuron level, at millisecond temporal resolution scale. Since scalp EEG contains considerable amount of noise and artifacts and exactly where it is coming from is poorly determined, extracting information from it is extremely challenging. For this reason it is necessary to design specific filters to decrease such artifacts in EEG records. Approach: Some of the other methods that are really appealing are artifact removal through Independent Component Analysis (ICA), Wavelet Transforms, Linear filtering and Artificial Neural Networks. ICA method could be used in situations, where large numbers of noises need to be distinguished, but it is not suitable for on-line real time application like Brain Computer Interface (BCI). Wavelet transforms are suitable for real-time application, but there all success lies in the selection of the threshold function. Linear filtering is best when; the frequency of noises does not interfere or overlap with each other. In this study we proposed adaptive filtering and neuro-fuzzy filtering method to remove artifacts from EEG. Adaptive filter performs linear filtering. Neuro-fuzzy approaches are very promising for non-linear filtering of noisy image. The multipleoutput structure is based on recursive processing. It is able to adapt the filtering action to different kinds of corrupting noise. Fuzzy reasoning embedded into the network structure aims at reducing errors when fine details are processed. Results: The computational result shows that the artifacts from the EEG are removed to a great extent and this has led to the accurate analysis and diagnosis of the EEG related diseases. Conclusion: Experimental results show that the proposed neuro-fuzzy technique is very effective and performs significantly better. The fidelity of the reconstructed EEG signal is assessed quantitatively using parameters such as Signal to Noise Ratio (SNR) and Power Spectral Density (PSD). In addition we have also compared the performance of adaptive filter and neuro-fuzzy filter based on the above parameters.

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“…The publication in (Alfred, 2010) summarized the relational data using semi-supervised genetic algorithm-based clustering techniques. The study in (Furukawa, 2010) presented an adaptable user interface which is based on the ecological interface design concept for multiple robots operating with uncertainty. The study in (Mohammed et al, 2010) aimed at presenting principal attacks classifications, especially the study of classification towards evaluation for which suggested some improvements that may allow the generation of test cases selection about attacks by using the classification tree method.…”

Section: Introductionmentioning

confidence: 99%

Petri Nets and Ladder Logic for Fully-Automating and Programmable Logic Control of Semi-Automatic Machines and Systems

Barghash¹,

Abuzeid²,

Al‐Rabadi³

et al. 2011

American Journal of Engineering and Applied Sciences

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Problem statement: Automating semi-automatic dynamic machines and complex systems, where some functionalities are already automated but the machine doesn't run fully in automatic mode, represents another challenge to automating dynamic and manual complex systems. This study deals with a special case of this general problem, where the system's semi-automatic and automatic functionalities run separately in a sequence with either automatic and/or semi-automatic functionality running at any point of time, but not both. Approach: Petri-nets can successfully represent the operations of both the semi-automated and fully-automated functionalities of such dynamic systems. Three roles for the programmable logic controllers were suggested: (a) Ignoring the presence of the semi-automatic part, (b) simulating the semi-automatic part and recognizing discrepancies and(c) simulating the semi-automatic functionalities and supporting it, where the last choice was most costly and most reliable. Results: This study presents a case study for a PVC mixing dynamic process to illustrate the three suggested controller design possibilities, where a Petri net model and related ladder logic program were developed to show these three controller design options. In this respect, the semiautomatic functionality is an intermediate step between the two automated functionalities, within which an important decision should be made to end the previous automatic step and to begin the next automatic step. Conclusion/Recommendations: The automation method that was introduced in this study is applicable to a large number of machines within industrial and mechanical systems that were built using older semi-automatic control systems. Various decision analyses {DA1, DA2, DA3} were shown to produce basic choices for such types of applications. Petri-nets and ladder logic in this respect can successfully represent the operations of both the semi-automated and fully-automated functionalities, where a Petri net model and the consequent ladder logic program, used to program the utilized programmable logic controller, are developed to show three possible controller designs, where the choice between three designs depend on the designers objective of cost, reliability and fault tolerance.

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Adaptable User Interface Based on the Ecological Interface Design Concept for Multiple Robots Operating Works with Uncertainty

Cited by 8 publications

References 18 publications

Optimization of Clustering Time by a Group of Autonomous Robots Making Use of an Exclusive Multi-Marking

Optimization of Clustering Time by a Group of Autonomous Robots Making Use of an Exclusive Multi-Marking

Comparative Evaluation of Adaptive Filter and Neuro-Fuzzy Filter in Artifacts Removal From Electroencephalogram Signal

Petri Nets and Ladder Logic for Fully-Automating and Programmable Logic Control of Semi-Automatic Machines and Systems

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