Streaming Media

Subject Area

Mechanical Engineering

Abstract

Modular reconfigurable robots, with on-demand assembly and disassembly, offer the possibility of mesoscale (milli- and microscale) manufacturing. However, most of the existing modular robotic platforms currently being designed and functionalized rely on complex actuation and assembly mechanisms and so lack further scalability and transformability required for mesoscale applications. Therefore, this dissertation seeks to develop a novel scalable modular robotic platform with controlled self-assembly, disassembly, and reconfiguration techniques using an external electromagnetic field. While current cutting-edge research in this area uses a single magnet to move one module at a time into the target position, this dissertation explores processes to move swarms of modules with global magnetic control inputs and reconfigure them with boundary collision. This dissertation presents for the first time the scalable modular robots and their deterministic self-assembly, disassembly, and reconfiguration techniques for constructing user-specified structures with wireless control. A detailed analysis of the module design, motion dynamics, and the modular robots’ time-optimal self-assembly and reconfiguration techniques under the open-loop and closed-loop control methods is presented here. The modular robots are designed as scalable 3D-printed cubic bodies with permanent magnets embedded in their faces or encapsulated inside the body. The magnets allow spatial variation of magnetic properties in the modular subunits, act as a coupling mechanism, enable an untethered and onboard circuit-free actuation method, and ensure controllable task-specific reconfiguration. This novel design of the modular robotic platform and its precisely controlled self-assembly/disassembly mechanism could be used to simplify and upgrade the capabilities of existing mesoscale manufacturing and manipulation technologies.

Degree Date

Spring 5-13-2023

Document Type

Dissertation

Degree Name

Ph.D.

Department

Mechanical Engineering

Advisor

Dr. MinJun Kim

Second Advisor

Dr. Ali Beskok

Third Advisor

Dr. Paul S. Krueger

Fourth Advisor

Dr. Wei Tong

Fifth Advisor

Dr. Aaron T. Becker

Number of Pages

155

Format

.pdf

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Available for download on Sunday, May 04, 2025

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