Design, Fabrication and Experimental Validation of a Steerable, Laser-Driven Microrobot in Dry Environments

Zhong, Yi; Sherehiy, Andriy; Chowdhury, Sri Sukanta; Wei, Danming; Zhang, Ruoshi; Popa, Dan O.

doi:10.1109/case48305.2020.9216958

Cited by 4 publications

(7 citation statements)

References 16 publications

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Section: Thermal Actuatorsmentioning

confidence: 99%

“…The power is delivered to these actuators by directing light onto photovoltaic cells on the top of the mobile microbot. [ 102,113 ] Moreover, Zhong et al [ 105 ] presented a laser‐driven microbot that utilizes two Z‐shaped silicon actuators. The movement of this microbot is induced by using a pulsing laser beam to heat up the serpentine microstructures, as shown in Figure 6i, while the driving force is controlled by tuning the beam frequency.…”

Section: Thermal Actuatorsmentioning

confidence: 99%

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Actuation of Mobile Microbots: A Review

Hussein,

Damdam,

Ren

et al. 2023

Advanced Intelligent Systems

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Maturation of robotics research and advances in the miniaturization of machines have contributed to the development of microbots and enabled new technological possibilities and applications. Microbots have a wide range of applications, including the navigation of confined spaces, environmental monitoring, micro‐assembly and manipulation of small objects, and in vivo micro‐surgeries and drug delivery. Actuators are among the most critical components that define the performance of robots. A comprehensive review of the actuation mechanisms that have been employed in mobile microbots is provided, including piezoelectric, magnetic, electrostatic, thermal, acoustic, biological, chemical, and optical actuation, with a focus on the most recent development and methodologies.

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Section: Thermal Actuatorsmentioning

confidence: 99%

Section: Thermal Actuatorsmentioning

confidence: 99%

Actuation of Mobile Microbots: A Review

Hussein,

Damdam,

Ren

et al. 2023

Advanced Intelligent Systems

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“…SerpenBot is a laser-driven microrobot that shares locomotion principles with its predecessor, the ChevBot [27][28][29][30]. The SerpenBot has two asymmetrical thermal actuators, called Elbow Thermal Actuator (ETA), implemented as legs shown in Fig.…”

Section: Serpenbot Fabricationmentioning

confidence: 99%

“…The resulting microrobot has a body with approximate dimension 647 𝜇𝑚 by 445 𝜇𝑚 , with serpentine width 5 𝜇𝑚 and 9 turns. This design is based on the consideration of the laser spot size, power, and pulse frequency, as detailed by our previous publications [26][27][28][29][30][31]. System Modeling…”

Section: Serpenbot Fabricationmentioning

confidence: 99%

“…The laser enables motion and steering control as well acting as a power supply, [26,27,28]. In our previous preliminary studies, we have shown that steering control of microrobots in dry environments can be realized in two ways: 1) tuning laser frequency [29,30], and 2) controlling the off-axis location for selective irradiation of the robot's body. In this work, we focused on the latter method and experimentally validate driving and steering motions of SerpenBots toward a goal.…”

Section: Introductionmentioning

confidence: 99%

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Learning Control of a Laser-Driven Locomotive Microrobot for Dry Environments

Zhong

Alqatamin

Sherehiy

et al. 2022

Preprint

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In this paper, we introduce the SerpenBot, a microrobot smaller than 1mm in size, powered by laser energy, and designed to operate in dry environments. The microrobot achieves locomotion on a Si substrate by selective coupling of laser energy between two legs that move the robot forward and steer it. The laser energy coupling mechanism is achieved by selective energy-time irradiation of the microrobot’s body and legs to initiate the gait. Complex multi-physics models developed in our past work are simplified to a differential drive kinematic model that approximates the robot behavior and is used to formulate a deep learning controller that can steer the robot to desired locations on the silicon substrate. Simulations predict the robot position regulation achieved by deep learning of the inverse robot Jacobian. Experimental results are presented confirming that the microrobot can be automatically steered to a goal location.

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