Design, Simulation, and Programming of Magnetic Soft Robots
Creators: name: Karacakol, Alp Can
Publisher: name: Carnegie Mellon University
Year: 2023
Subjects: Applied Computer Science

description: Soft robots have emerged as a new branch of robotics with deformable bodies to achieve adaptability to dynamically changing unstructured environments and safe interaction with life forms ranging from cells to humans. The miniaturization efforts in soft robotics for operation in enclosed, small, and remote spaces led to the development of stimuli-responsive soft robots where the actuation mechanism relies on the encoded response of the robot body to the external stimuli at the material level. Among the wide range of proposed external stimuli of temperature, light, chemical, and electric and magnetic fields, magnetic fields are exceptionally promising due to their safe and transparent interaction around biological tissues. The magnetically responsive soft robots or, in short, magnetic soft robots present untethered, fast, and reversible actuation at small scales within confined environments, making them ideal candidates for minimally invasive clinical operations within the human body. While the anticipated applications and impact of magnetic soft robots are exciting, various challenges are associated with the programming of the magnetic response, the prediction of the resultant magnetic response, and the design of the robot structure and magnetic encoding, requiring the development of novel strategies. In this thesis, a magnetic programming method, simulation approaches for predicting magnetic responses, and a data-driven strategy for the design of robot structure and magnetic encoding are introduced to develop the fundamentals of magnetic soft robots, addressing the pressing issues. A novel magnetic programming strategy is presented based on heating magnetic soft materials above the Curie temperature of the embedded ferromagnetic particles and aligning the magnetic domains by applying magnetic fields in the desired direction. The proposed method comprehensively demonstrates discrete, three-dimensional, high-throughput, and reprogrammable magnetization at high spatial resolution addressing the limitations of the existing magnetic programming approaches. To address the non-intuitive design challenge, a systematic and experience-free data-driven design approach is proposed to spatially program morphology and 3D magnetic profile of magnetic soft robots for desired behaviors. Our design strategy relying on the developed computationally low-cost simulation engine reveals complex magnetic soft robot behaviors that were unattainable. The best-performing designs are experimentally realized via the introduced magnetic programming method, showcasing the <em>sim2real</em> transfer. In addition, a dynamic faster-than-real-time simulation framework based on the discrete elastic rod method is introduced to accelerate the design and control endeavors in magnetic soft robots. The developed framework is validated rigorously for 2D and 3D quasi-static and dynamic conditions and captures the fundamental bending, twisting, and buckling behavior of the magnetic soft robots.