An Algorithm Based on the Bacterial Swarm and Its Application in Autonomous Navigation Problems

Sarmiento, Fredy Hernán Martínez; Rendón, Angélica; Arbulú, Mario

doi:10.1007/978-3-319-93815-8_30

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…This research proposes an intelligent tuning strategy of a PID controller for a system with disturbances based on the idealized behavior of bacteria, including their QS to reduce the convergence time (Martínez, Rendón, and Arbulú, 2018;Jacinto, Giral, and Martìnez, 2016). The strategy is implemented and evaluated by simulation.…”

Section: Conclusionesmentioning

confidence: 99%

PID controller tuning using bacterial Quorum Sensing (QS)

Sarmiento¹,

Soto²

2020

Tecnura

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Objective: PID controllers are widely used to operate AC motors due to their simplicity and easy implementation. However, adjusting its parameters in search of an optimal scheme can be complex because it requires manual tuning by trial and error. This research aims to implement an optimized tuning scheme through a search based on the idealized behavior of a community of bacteria and its Quorum Sensing (QS). Methodology: A closed-loop system model with PID control considering disturbances is proposed in order to tune a disturbance-resistant controller. The response of the model is calculated using a search that mimics a simplified model of bacterial behavior. The scheme uses ITSE (Integral Time Squared Error) as the performance index. Results: The tuning resulting from the proposed scheme was evaluated by simulation and compared with tunings of the same model made by Root Locus and Genetic Algorithms (GA). The results showed a satisfactory response according the design criteria. Conclusions: Nowadays, PID controllers are still basic industrial control tools, particularly important in motor operation. The performance of these controls depends fundamentally on the design of their gain. In the case of complex plants, additional tools are required to facilitate PID tuning. We propose an intelligent and bio-inspired tuning scheme that demonstrates high performance in laboratory tests. Financing: University Francisco José de Caldas through the project 1-72-578-18.

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Section: Conclusionesmentioning

confidence: 99%

PID controller tuning using bacterial Quorum Sensing (QS)

Sarmiento¹,

Soto²

2020

Tecnura

Self Cite

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“…As applied research the research group has studied the problem of safe grasping of cylindrical objects with anthropomorphic hands [25], considering also the delicate interaction with humans. We have also developed many autonomous navigation schemes for locally observable dynamic environments [26][27][28][29], and analyzed the problem of dynamic bipedal walking [30]. All these are current unsolved problems of healthcare robotics, which seek to be integrated into the development of more complex tasks such as the monitoring of vital signs in patients, administration of food and medicine or immediate attention in case of emergencies.…”

Section: Introductionmentioning

confidence: 99%

Identifier of human emotions based on convolutional neural network for assistant robot

2020

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This paper proposes a solution for the problem of continuous prediction in real-time of the emotional state of a human user from the identification of characteristics in facial expressions. In robots whose main task is the care of people (children, sick or elderly people) is important to maintain a close relationship man-machine, anld a rapid response of the robot to the actions of the person under care. We propose to increase the level of intimacy of the robot, and its response to specific situations of the user, identifying in real time the emotion reflected by the person's face. This solution is integrated with algorithms of the research group related to the tracking of people for use on an assistant robot. The strategy used involves two stages of processing, the first involves the detection of faces using HOG and linear SVM, while the second identifies the emotion in the face using a CNN. The strategy was completely tested in the laboratory on our robotic platform, demonstrating high performance with low resource consumption. Through various controlled laboratory tests with different people, which forced a certain emotion on their faces, the scheme was able to identify the emotions with a success rate of 92%.

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An Algorithm Based on the Bacterial Swarm and Its Application in Autonomous Navigation Problems

Cited by 2 publications

References 6 publications

PID controller tuning using bacterial Quorum Sensing (QS)

PID controller tuning using bacterial Quorum Sensing (QS)

Identifier of human emotions based on convolutional neural network for assistant robot

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