Recently, robots have assisted and contributed to the biomedical field. Scaling down the size of robots to micro/nanoscale can increase the accuracy of targeted medications and decrease the danger of invasive operations in human surgery. Inspired by the motion pattern and collective behaviors of the tiny biological motors in nature, various kinds of sophisticated and programmable microrobots are fabricated with the ability for cargo delivery, bio-imaging, precise operation, etc. In this review, four types of propulsion—magnetically, acoustically, chemically/optically and hybrid driven—and their corresponding features have been outlined and categorized. In particular, the locomotion of these micro/nanorobots, as well as the requirement of biocompatibility, transportation efficiency, and controllable motion for applications in the complex human body environment should be considered. We discuss applications of different propulsion mechanisms in the biomedical field, list their individual benefits, and suggest their potential growth paths.

One major challenge for microrobots is to penetrate and effectively move through viscoelastic biological tissues. Most existing microrobots can only propel in viscous liquids. Recent advances demonstrate that sub-micron robots can actively penetrate nanoporous biological tissue, such as the vitreous of the eye. However, it is still difficult to propel a micron-sized device through dense biological tissue. Here, we report that a special twisted helical shape together with a high aspect ratio in cross-section permit a microrobot with a diameter of hundreds-of-micrometers to move through mouse liver tissue. The helical microrobot is driven by a rotating magnetic field and localized by ultrasound imaging inside the tissue. The twisted ribbon is made of molybdenum and a sharp tip is chemically etched to generate a higher pressure at the edge of the propeller to break the biopolymeric network of the dense tissue.

Microrobotics has opened new horizons for various applications, especially in medicine. However, it also witnessed challenges in achieving maximum optimal performance. One key challenge is the intelligent, autonomous, and precise navigation control of microrobots in fluid environments. The intelligence and autonomy in microrobot control, without the need for prior knowledge of the entire system, can offer significant opportunities in scenarios where their models are unavailable. In this study, two control systems based on model-free deep reinforcement learning were implemented to control the movement of a disk-shaped magnetic microrobot in a real-world environment. The training and results of an off-policy SAC algorithm and an on-policy TRPO algorithm revealed that the microrobot successfully learned the optimal path to reach random target positions. During training, the TRPO exhibited a higher sample efficiency and greater stability. The TRPO and SAC showed 100% and 97.5% success rates in reaching the targets in the evaluation phase, respectively. These findings offer basic insights into achieving intelligent and autonomous navigation control for microrobots to advance their capabilities for various applications.

Light sensing and communication represent a vital link in the progress of biological evolution, helping organisms to respond to their environment and carry out survival activities. To simulate this process and exploit it in engineering applications, we develop a light-driven micro/nanorobotic system. Like the natural defense mechanisms of biological vision, these robots can mimic the sensitivity and responsiveness of living organisms to light stimuli. Additionally, the development of nanotechnology and molecular communication (MC) caters to the trend of the Internet of Bio-Nano Things. However, there are still difficulties in conducting systematic research at the experimental level in related scientific fields. To bridge the gap between the simulation of MC with micro/nanorobots and the construction of an experimental testbed, a complete micro/nano-scale communication platform is built by using customized optical microscopy equipment. We use $\text{Cu}_{2}\text{O}$ micro/nanorobots to imitate the natural properties of molecules, since under negative phototactic motion they are suitable for being a message carrier in MC. This is similar to the behavior of visual organisms that receive external light stimuli and convert them into biomolecular signals. Information is transmitted by controlling the self-driving of the micro/nanorobots with in-situ signals. We propose three low-complexity threshold-based detectors to recover information from the received signal. Experimental results show that the light-driven micro/nanorobots can meet the requirements of multi-directional manipulation. Through the implemented miniaturized observation testbed coupled with light-driven micro/nanorobots, microparticle-based information transmission is accomplished by utilizing the properties of micro/nanorobots.

Micro/nanorobots (MNRs) are untethered, small‐scale devices designed to perform complex tasks in challenging and inaccessible environments, with promising biomedicine and environmental remediation applications. Recent advancements in multi‐module MNRs, which incorporate functional components such as actuators, propellers, imaging modalities, and manipulators, have significantly expanded their capabilities while addressing the limitations of single‐module designs. This article reviews recent progress in these core modules, emphasizing their application in biomedicine, including targeted drug delivery, tissue repair, and diagnosis, as well as in environmental remediation, such as pollutant removal and microorganism treatment. It highlights practical strategies to address real‐world challenges in these domains, with a focus on the multi‐module design in enhancing functionality. Despite substantial advancements, key challenges persist, including scalability, real‐time imaging, and intelligent control. Future research directions include the development of intelligent modules equipped with memory, data processing, and communication functions, enabling autonomous decision‐making and closed‐loop control. These developments hold the potential to foster innovation in medicine, environmental sustainability, and other critical fields.