Microrobots in Micromachines

Fortuna, Luigi; Buscarino, Arturo

doi:10.3390/mi13081207

Cited by 3 publications

(1 citation statement)

References 20 publications

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“…Optical tweezers, which use light to manipulate micro-objects, can play an important role in actuating these microtools. There has previously been research on using different types of microbots in micromachines [72]. The feasibility of using light in micro actuation has already been demonstrated [73][74][75].…”

Section: Micro Manipulationmentioning

confidence: 99%

Light-Controlled Microbots in Biomedical Application: A Review

2022

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The advancement of micro-robotics in recent years has permitted a vast field of active research and application in the biomedical sector. Latest developments in microrobotics point to some ground-breaking work using light for manufacturing as well as actuation. Optical manipulation in three-dimensional space for living biological cells in a minimally invasive manner is crucial for different biomedical applications. This article attempts to provide an overview of the accomplishments and future possibilities of light-powered microbots. An overview of the feasibility of different fabrication techniques and control modalities is compared, along with prospective applications and design considerations of light-powered microbots. A variety of challenges that still prohibit polymeric light-powered microbots from attaining their full potential are pointed out, and viable ways to overcome such challenges are proposed. This study will help future researchers to study and develop the next generation of light-actuated microbots by overcoming the current limitations and challenges in fabrication, control, and design.

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Section: Micro Manipulationmentioning

confidence: 99%

Light-Controlled Microbots in Biomedical Application: A Review

2022

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Improving the Quality of Industrial Robot Control Using an Iterative Learning Method with Online Optimal Learning and Intelligent Online Learning Function Parameters

Ha,

Thuong,

Vinh

2024

Applied Sciences

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It is inevitable that the characteristics of a robot system change inaccurately or cannot be accurately determined during movement and are affected by external disturbances. There are many adaptive control methods, such as the exact linearization method, sliding control, or neural control, to improve the quality of trajectory tracking for a robot’s motion system. However, those methods require a great deal of computation to solve the constrained nonlinear optimization problem. This article first presents some techniques for determining the online learning function parameters of an intelligent controller, including two circuits: the inner circuit is an uncertain function component estimator to compensate for the robot’s input, and the outer circuit is an iterative learning controller and does not use a mathematical model of the robot with optimal online learning function parameters. The optimal condition is based on the model in the time domain to determine the learning function parameters that change adaptively according to the sum of squared tracking errors of each loop. As for the intelligent online learning function parameters, they closely follow the general model to stabilize the robot system, based on the principle of intelligent estimation of the uncertainty component and total noise. This method is built on Taylor series analysis for the state vector and does not use a mathematical model of the system at all. It allows feedback linearization, as well as intelligent stabilization of the system. This article’s content uses a 2-DOF flat robot implemented on MatlabR2022b software to verify the theory. These findings indicate that superior tracking performance is achievable.

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Impact Attenuator Design for Improvement of Racing Car Drivers’ Safety

Itu

Vlase

2023

Symmetry

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An essential element for driver safety is represented by the Impact Attenuator (especially for race cars). The effect of the Impact Attenuator can be seen in the behavior of a dummy, tied with a seat belt, in a frontal collision with a rigid wall. The loads that act on the dummy are determined and checked to see if they fall within the values recommended by existing standards. The car is considered a structure with a dummy fixed with a seat belt and equipped with an Impact Attenuator. Two types of Impact Attenuator having constructive similarity and symmetries are studied, made up of three different materials and different thicknesses of material. The behavior of the dummy was studied, considering a frontal collision of the car–dummy assembly, in accordance with existing standards. Using simulation software, the accelerations were determined at various points on the mannequin’s body and the force appearing on the seat belts was determined. The Gibbs–Appell equations are the method used to determine the dynamic response in this problem involving shocks.

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Microrobots in Micromachines

Abstract: Robotics and micromachines are challenging topics in engineering [...]

Cited by 3 publications

References 20 publications

Light-Controlled Microbots in Biomedical Application: A Review

Light-Controlled Microbots in Biomedical Application: A Review

Improving the Quality of Industrial Robot Control Using an Iterative Learning Method with Online Optimal Learning and Intelligent Online Learning Function Parameters

Impact Attenuator Design for Improvement of Racing Car Drivers’ Safety

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