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Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

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Bat algorithm based control to decrease the control energy consumption and modified bat algorithm based control to

José de Jesús Rubio¹

¹Sección de Estudios de Posgrado e Investigación, ESIME Azcapotzalco, Instituto Politécnico Nacional, Av. de las Granjas no. 682, Col. Santa Catarina, Ciudad de México, 02250, Mexico.

Neural Networks : the Official Journal of the International Neural Network Society

|February 22, 2023

Summary

This summary is machine-generated.

This study introduces bat algorithm-based robot control to optimize control gain. The proposed methods aim to reduce energy consumption and enhance trajectory tracking accuracy, outperforming simplex-based control.

Keywords:

Bat algorithm based control Control energy consumption Modified bat algorithm based control Robots Simplex algorithm based control Trajectory tracking accuracy

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Area of Science:

Robotics
Control Theory
Artificial Intelligence

Background:

Optimizing robot control gain is crucial for balancing trajectory tracking accuracy and energy consumption.
The bat algorithm offers a random search approach for finding optimal control gains.
Existing control methods may not sufficiently address both accuracy and energy efficiency.

Purpose of the Study:

To propose a bat algorithm-based control strategy to minimize robot control energy consumption.
To introduce a modified bat algorithm-based control for improving robot trajectory tracking accuracy.
To compare the performance of the proposed bat algorithm controls against simplex-based control.

Main Methods:

Developing a bat algorithm to identify optimal control gains for reduced energy usage.
Modifying the bat algorithm to enhance trajectory tracking precision in robotic systems.
Conducting comparative analyses of proposed bat algorithm controls and simplex-based control using two robots.

Main Results:

The bat algorithm-based control effectively decreased control energy consumption in robots.
The modified bat algorithm-based control significantly increased trajectory tracking accuracy.
Both proposed bat algorithm controls demonstrated superior performance compared to simplex-based control in specific metrics.

Conclusions:

Bat algorithm-based control is a viable method for optimizing robot control gain.
The proposed strategies offer improved solutions for energy efficiency and trajectory tracking in robotics.
Further research can explore advanced modifications of the bat algorithm for complex robotic applications.