Artificial Intelligence Meets Micro/Nanorobotics

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Authors

Institutions

Publication Details

Journal
Advanced Materials
Published
2026-08-27
DOI
https://doi.org/10.1002/adma.74721
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial Intelligence Meets Micro/Nanorobotics

Cherukutty Ramakrishnan Minitha, Martin Pumera, Michal Otyepka, Hamed Shahsavan et al.
Advanced Materials
Micro and Nano Robotics
article

Artificial Intelligence Meets Micro/Nanorobotics

Cherukutty Ramakrishnan Minitha, Martin Pumera, Michal Otyepka, Hamed Shahsavan, Fatma M. Yurtsever, Ivan Zelinka, Ian Kuula Ross
article en

Abstract

Microrobots and nanorobots are a developing technology, which evolved from simple "motoric" motion-capable micro/nanomachines to physical machine intelligence capable of communicating with each other using chemical or physical signals. Meanwhile, artificial intelligence (AI) is rapidly integrating into our modern life. We explore here how AI can be implemented in micro- and nanorobotic systems. The advancement of AI enhances micro- and nanorobots' performance but also drives a fundamental transition from externally actuated, task-specific platforms toward autonomous, adaptive, and multifunctional systems capable of operating in highly complex environments for clinical and environmental applications. At the micro/nanoscale, propulsion, sensing, and control face several limitations, including limited onboard computation, which hinder deterministic navigation and task execution. Recent advances in machine learning, including deep learning, reinforcement learning, and physics-informed models, now offer powerful solutions to overcome those limitations. This perspective highlights how the convergence of AI and micro- and nanorobot technologies is creating a promising hybrid discipline for translational applications in both clinical and environmental settings. AI-assisted design accelerates the discovery of functional materials tailored to specific applications, optimizes geometric and surface properties for efficient propulsion, and enables generative fabrication of micro- and nanorobot architectures. Moreover, deep learning-based ultrasound, optical depth estimation, and multimodal perception enable precise real-time localization-an essential requirement for closed-loop autonomythereby enhancing the imaging and tracking of micro- and nanorobots. Additionally, the use of digital twins offers a predictive model of real-world experimentation supporting risk assessment and patient-specific planning for biomedical applications. The advances in AI-enhanced micro- and nanorobots will transform the targeted drug delivery, minimally invasive diagnostics, biosensing, environmental remediation, and pollutant capture by integrating real-time perception and adaptive decision-making into fully autonomous devices in complex clinical and environmental conditions.

Advanced Materials
VSB - Technical University of Ostrava (CZ), Asia University (TW), University of Waterloo (CA), Yonsei University (KR), Central European Institute of Technology (AT), Regional Centre of Advanced Technologies and Materials (CZ), Palacký University Olomouc (CZ)
European Commission, Grantová Agentura České Republiky, European Regional Development Fund, European Social Fund
Openalex Percentile: Top 15%
Micro and Nano Robotics
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