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Advancing Self-Burrowing Soft Robots...

Lee, Hyunjin,

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Advancing Self-Burrowing Soft Robots: Cone Probe Burrowing Model and Bio-Inspired Strategies /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Advancing Self-Burrowing Soft Robots: Cone Probe Burrowing Model and Bio-Inspired Strategies // Hyunjin Lee.
作者:	Lee, Hyunjin,
面頁冊數:	1 electronic resource (127 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-02, Section: B.
Contained By:	Dissertations Abstracts International86-02B.
標題:	Geotechnology. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31488200
ISBN:	9798384020639

Advancing Self-Burrowing Soft Robots: Cone Probe Burrowing Model and Bio-Inspired Strategies /
Lee, Hyunjin,

Advancing Self-Burrowing Soft Robots: Cone Probe Burrowing Model and Bio-Inspired Strategies /Hyunjin Lee. - 1 electronic resource (127 pages)

Source: Dissertations Abstracts International, Volume: 86-02, Section: B.

Self-burrowing soft robots have attracted considerable attention in recent years due to their potential applications in various fields such as geotechnical engineering, environmental monitoring, and site exploration. However, the intricate interactions between the robots and the soil along with the limitations of soft actuators present significant challenges when it comes to designing and controlling these robots. This dissertation aims to address these challenges by developing an analytical model for the cone probe burrowing process and by proposing a novel bio-inspired burrowing strategy that can be applied to the cone probe. Both approaches are designed to enhance the functionality of self-burrowing soft robots, with the cone probe being a common structural component in many of their prototypes.This study focuses on developing an analytical model for cone probe burrowing, addressing both vertical and steering processes. The model utilizes the cavity expansion theory to simulate the interaction between the soil and the cone probe. To capture the effects of cone geometry, the theory is modified. The vertical burrowing model is shown to be practical and effective. Extending the model framework to include steering, the study addresses the interaction changes due to the non-contact area that emerges during steering. The model predicts the forces and moments required for burrowing, considering the path's curvature and the cone probe's geometry. The proposed model is assessed through numerical simulations and experimental tests with modeling clay, demonstrating the model's reliable predictive capabilities.Furthermore, this dissertation introduces a novel bio-inspired burrowing strategy called the "morphing cone strategy." Inspired by the shape-changing abilities of worm-like organisms, the morphing cone strategy adaptively changes the cone head's geometry to reduce penetration resistance and enhance burrowing efficiency. Numerical simulations demonstrate the effectiveness of this strategy in reducing energy consumption and suggest that it may also improve the overall performance of self-burrowing soft robots.The findings of this research provide valuable insights for the design and control of self-burrowing soft robots, offering a framework for translating biological burrowing mechanisms into engineering solutions. The proposed models and strategies pave the way for the development of highly efficient and adaptable robots for a wide range of applications. Future research could extend these models to include various soil behaviors, integrate sensing and control systems, and explore multi-segment designs through prototype experiments, ultimately advancing the field of self-burrowing soft robotics and enabling new possibilities for subsurface exploration.

English

ISBN: 9798384020639Subjects--Topical Terms:

1018558
Geotechnology.
Subjects--Index Terms:

Bio-inspired strategies

Advancing Self-Burrowing Soft Robots: Cone Probe Burrowing Model and Bio-Inspired Strategies /
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520 $a Self-burrowing soft robots have attracted considerable attention in recent years due to their potential applications in various fields such as geotechnical engineering, environmental monitoring, and site exploration. However, the intricate interactions between the robots and the soil along with the limitations of soft actuators present significant challenges when it comes to designing and controlling these robots. This dissertation aims to address these challenges by developing an analytical model for the cone probe burrowing process and by proposing a novel bio-inspired burrowing strategy that can be applied to the cone probe. Both approaches are designed to enhance the functionality of self-burrowing soft robots, with the cone probe being a common structural component in many of their prototypes.This study focuses on developing an analytical model for cone probe burrowing, addressing both vertical and steering processes. The model utilizes the cavity expansion theory to simulate the interaction between the soil and the cone probe. To capture the effects of cone geometry, the theory is modified. The vertical burrowing model is shown to be practical and effective. Extending the model framework to include steering, the study addresses the interaction changes due to the non-contact area that emerges during steering. The model predicts the forces and moments required for burrowing, considering the path's curvature and the cone probe's geometry. The proposed model is assessed through numerical simulations and experimental tests with modeling clay, demonstrating the model's reliable predictive capabilities.Furthermore, this dissertation introduces a novel bio-inspired burrowing strategy called the "morphing cone strategy." Inspired by the shape-changing abilities of worm-like organisms, the morphing cone strategy adaptively changes the cone head's geometry to reduce penetration resistance and enhance burrowing efficiency. Numerical simulations demonstrate the effectiveness of this strategy in reducing energy consumption and suggest that it may also improve the overall performance of self-burrowing soft robots.The findings of this research provide valuable insights for the design and control of self-burrowing soft robots, offering a framework for translating biological burrowing mechanisms into engineering solutions. The proposed models and strategies pave the way for the development of highly efficient and adaptable robots for a wide range of applications. Future research could extend these models to include various soil behaviors, integrate sensing and control systems, and explore multi-segment designs through prototype experiments, ultimately advancing the field of self-burrowing soft robotics and enabling new possibilities for subsurface exploration.
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650 4 $a Geotechnology. $3 1018558
650 4 $a Environmental engineering. $3 548583
650 4 $a Robotics. $3 519753
653 $a Bio-inspired strategies
653 $a Burrowing model
653 $a Self-burrowing soft robots
653 $a Locomotion
653 $a Penetration process
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690 $a 0428
690 $a 0775
690 $a 0771
710 2 $a Northwestern University. $b Civil and Environmental Engineering. $e degree granting institution. $3 3815791
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791 $a Ph.D.
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