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The integration of an ingestible dosage form with sensing, actuation, and drug delivery capabilities can enable a broad range of surgical‐free diagnostic and treatment strategies. However, the gastrointestinal (GI) tract is a highly constrained and complex luminal construct that fundamentally limits the size of an ingestible system. Recent advancements in mesoscale magnetic crawlers have demonstrated the ability to effectively traverse complex and confined systems by leveraging magnetic fields to induce contraction and bending‐based locomotion. However, the integration of functional components (e.g., electronics) in the proposed ingestible system remains fundamentally challenging. Herein, the creation of a centralized compartment in a magnetic robot by imparting localized flexibility (MR‐LF) is demonstrated. The centralized compartment enables MR‐LF to be readily integrated with modular functional components and payloads, such as commercial off‐the‐shelf electronics and medication, while preserving its bidirectionality in an ingestible form factor. The ability of MR‐LF to incorporate electronics, perform drug delivery, guide continuum devices such as catheters, and navigate air–water environments in confined lumens is demonstrated. The MR‐LF enables functional integration to create a highly integrated ingestible system that can ultimately address a broad range of unmet clinical needs. An interactive preprint version of the article can be found athttps://doi.org/10.22541/au.166274072.23086985/v1.
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A 3D‐Printed Self‐Learning Three‐Linked‐Sphere Robot for Autonomous Confined‐Space Navigation
Reinforcement learning control methods can impart robots with the ability to discover effective behavior, reducing their modeling and sensing requirements, and enabling their ability to adapt to environmental changes. However, it remains challenging for a robot to achieve navigation in confined and dynamic environments, which are characteristic of a broad range of biomedical applications, such as endoscopy with ingestible electronics. Herein, a compact, 3D‐printed three‐linked‐sphere robot synergistically integrated with a reinforcement learning algorithm that can perform adaptable, autonomous crawling in a confined channel is demonstrated. The scalable robot consists of three equally sized spheres that are linearly coupled, in which the extension and contraction in specific sequences dictate its navigation. The ability to achieve bidirectional locomotion across frictional surfaces in open and confined spaces without prior knowledge of the environment is also demonstrated. The synergistic integration of a highly scalable robotic apparatus and the model‐free reinforcement learning control strategy can enable autonomous navigation in a broad range of dynamic and confined environments. This capability can enable sensing, imaging, and surgical processes in previously inaccessible confined environments in the human body.
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- Award ID(s):
- 1830958
- PAR ID:
- 10370234
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Intelligent Systems
- Volume:
- 3
- Issue:
- 9
- ISSN:
- 2640-4567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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