Abstract
Micro/nanorobots have gained increasing attention worldwide owing to their promising potential in biomedicine. Benefiting from their small size and controllability, micro/nanorobots are ideal candidates for applications including targeted therapy, minimally invasive surgery, and drug delivery in physiological environments. However, the micro/nano-scale dimension hinders the ability and future application of miniature robots in the meantime. In recent years, swarm micro/nanorobotics has emerged as a rapidly developing interdisciplinary field. By simultaneously manipulating multiple micro/nanorobots, a micro/nanoswarm possesses larger delivery dose, better adaptivity to external environments, and better imaging contrast. Unlike macroscale robotic systems, implementing sensors or power supplies on micro/nanorobots is hard to achieve, which brings challenges for the control, feedback, and interagent communication of swarm micro/nanorobotics. In this review, we summarize state-of-the-art research about micro/nanoswarm, including actuation, imaging, and automatic control. Effective driving strategies and feedback methods provide the foundation for practical application. With the assistance of advanced control algorithms, micro/nanoswarms are able to exhibit computational intelligence. Compared to manual control, micro/nanoswarm systems with high-level autonomy is able to conduct bio-tasks with better efficiency and precision. Moreover, the future challenges and directions for micro/nanoswarms are discussed. With this review, we aim to provide a comprehensive understanding and valuable guidance for swarm micro/nanorobotics researchers.
| Original language | English |
|---|---|
| Pages (from-to) | 2338-2354 |
| Number of pages | 17 |
| Journal | IEEE/ASME Transactions on Mechatronics |
| Volume | 30 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Jun 2025 |
Keywords
- Automatic control
- deep learning
- medical imaging
- micro/nanorobots
- swarm micro/nanorobotics
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering