Chunxiang Wang

Last Name

Wang

First Name

Chunxiang

ORCID

0000-0002-6130-3553

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Publications1 - 5 of 5

3D-printed low-voltage-driven ciliary hydrogel microactuators
Liu, Zemin; Wang, Che; Ren, Ziyu; et al. (2026)
Nature
Micrometre-sized, densely packed natural cilia that perform non-reciprocal 3D motions with dynamically tunable collective patterns are crucial for biological processes such as microscale locomotion1, nutrient acquisition2, cell trafficking3,4,5 and embryonic and neurological development6,7,8. However, replicating these motions in artificial systems remains challenging given the limits of scalable, locally controllable soft-bodied actuation at the micrometre scale. Overcoming this challenge would enhance our understanding of ciliary dynamics, clarify their biological importance and enable new microscale devices and bioinspired technologies. Here we show a previously unrecognized fast electrical response of micrometre-scale hydrogels, induced by voltages down to 1.5 V without hydrolysis, with bending motions driven by ion migration across a nanometre-scale hydrogel network 3D-printed by two-photon polymerization, occurring within milliseconds. On the basis of these findings, we print gel microcilia arrays composed of a soft acrylic acid-co-acrylamide (AAc-co-AAm) hydrogel (modulus of approximately 1,000 Pa) that respond to electrical stimuli within milliseconds. Each microcilium measures 2–10 µm in diameter and 18–90 µm in height, achieving 3D rotational bending motion at up to 40 Hz, mirroring the geometry and dynamics of natural cilia. These gel microcilia maintain functionality after 330,000 continuous actuation cycles with less than 30% performance degradation. The gel microcilia arrays can be integrated on flexible polyimide substrates and fabricated at large scale using conventional lithography techniques. They also offer individual dynamic control by means of microelectrode arrays and enable fluid manipulation and particle transport at the micrometre scale.
Synthetic X‑ray‑driven tracking and control of miniature medical devices
Wang, Chunxiang; Kang, Wenbin; Sun, Mengmeng; et al. (2026)
Nature Machine Intelligence
The clinical translation of miniature medical devices (MMDs) for minimally invasive surgery promises transformative advances in biomedical engineering, offering enhanced precision, reduced patient trauma and faster recovery times. However, their effective deployment in complex anatomies under real-time X-ray guidance—a widely used surgical imaging modality—presents challenges such as low imaging quality and difficulties of spatial MMD control. Manual identification and operation are labour intensive and error prone. Meanwhile, deep learning-based automation is limited by the scarcity of annotated X-ray datasets of MMDs owing to costly data collection, laborious annotation and privacy constraints. Here we introduce MicroSyn-X, a framework for training computer vision models to enable robotic teleoperation of MMDs using synthesized high-fidelity, pixel-accurate, auto-labelled and domain-randomized X-ray images, eliminating manual data curation. Integrating MicroSyn-X into a teleoperated robotic system enables real-time localization and navigation of magnetic soft and magnetic liquid MMDs within both ex vivo and dynamic in vivo environments, demonstrating robustness under challenging imaging conditions of low contrast, high noise and occlusion. With these promises, we open source the X-ray MMD dataset to enable benchmarking. Addressing data scarcity and enabling real-time robotic navigation, this work advances MMD-assisted minimally invasive surgery towards next-generation precision interventions.
Synthetic Data-Assisted Miniature Medical Robot Navigation via Ultrasound Imaging
Wang, Chunxiang; Wang, Tianlu; Sitti, Metin (2025)
IEEE/ASME Transactions on Mechatronics
Wireless miniature robots are promising for minimally invasive biomedical applications. Effective tracking and navigation are essential for their safe deployment, but challenges persist in medical imaging and robot control, especially in localizing the robot in complex imaging scenes. Deep learning, though powerful for object identification, requires large supervised datasets, limiting its clinical applications due to the difficulty and cost of acquiring realistic data. Furthermore, miniature robots frequently exit the field of view of imaging systems, hindering continuous observation. Here, we present a framework for real-time magnetic navigation of wireless miniature robots using ultrasound imaging, leveraging synthetic data generation for deep learning-based detection. First, artificially generated synthetic data is combined with real data from synthetic materials to train a neural network capable of detecting versatile robots in real tissues. Then, a robotic system is developed to automatically track the robot with an ultrasound probe during magnetic actuation in tortuous lumens. With 85% less human-labeled data within synthetic materials, our approach effectively detects versatile robots in ex-vivo tissues, reducing data scarcity, imbalance, and manual labeling burdens. Demonstrations of automatic robot navigation through tortuous lumens in complex ultrasound scenes validate its effectiveness, enhancing the safe applicability of miniature medical robots in complex environments.
Heterogeneous multiple soft millirobots in three-dimensional lumens
Wang, Chunxiang; Wang, Tianlu; Li, Mingtong; et al. (2024)
Science Advances
Miniature soft robots offer opportunities for safe and physically adaptive medical interventions in hard-to-reach regions. Deploying multiple robots could further enhance the efficacy and multifunctionality of these operations. However, multirobot deployment in physiologically relevant three-dimensional (3D) tubular structures is limited by the lack of effective mechanisms for independent control of miniature magnetic soft robots. This work presents a framework leveraging the shape-adaptive robotic design and heterogeneous resistance from robot-lumen interactions to enable magnetic multirobot control. We first compute influence and actuation regions to quantify robot movement. Subsequently, a path planning algorithm generates the trajectory of a permanent magnet for multirobot navigation in 3D lumens. Last, robots are controlled individually in multilayer lumen networks under medical imaging. Demonstrations of multilocation cargo delivery and flow diversion manifest their potential to enhance biomedical functions. This framework offers a solution to multirobot actuation benefiting applications across different miniature robotic devices in complex environments.
Wireless flow-powered miniature robot capable of traversing tubular structures
Hong, Chong; Wu, Yingdan; Wang, Che; et al. (2024)
Science Robotics
Wireless millimeter-scale robots capable of navigating through fluid-flowing tubular structures hold substantial potential for inspection, maintenance, or repair use in nuclear, industrial, and medical applications. However, prevalent reliance on external powering constrains these robots’ operational range and applicable environments. Alternatives with onboard powering must trade off size, functionality, and operation duration. Here, we propose a wireless millimeter-scale wheeled robot capable of using environmental flows to power and actuate its long-distance locomotion through complex pipelines. The flow-powering module can convert flow energy into mechanical energy, achieving an impeller speed of up to 9595 revolutions per minute, accompanied by an output power density of 11.7 watts per cubic meter and an efficiency of 33.7%. A miniature gearbox module can further transmit the converted mechanical energy into the robot’s locomotion system, allowing the robot to move against water flow at an average rate of up to 1.05 meters per second. The robot’s motion status (moving against/with flow or pausing) can be switched using an external magnetic field or an onboard mechanical regulator, contingent on different proposed control designs. In addition, we designed kirigami-based soft wheels for adaptive locomotion. The robot can move against flows of various substances within pipes featuring complex geometries and diverse materials. Solely powered by flow, the robot can transport cylindrical payloads with a diameter of up to 55% of the pipe’s diameter and carry devices such as an endoscopic camera for pipeline inspection, a wireless temperature sensor for environmental temperature monitoring, and a leak-stopper shell for infrastructure maintenance.

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Chunxiang Wang

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