Autonomous environment-adaptive microrobot swarm navigation enabled by deep learning-based real-time distribution planning

Oral administration microrobots for drug delivery

Oral administration is the most simple, noninvasive, convenient treatment. With the increasing demands on the targeted drug delivery, the traditional oral treatment now is facing some challenges: 1) biologics how to implement the oral treatment and ensure the bioavailability is not lower than the subcutaneous injections; 2) How to achieve targeted therapy of some drugs in the gastrointestinal tract? Based on these two issues, drug delivery microrobots have shown great application prospect in oral drug delivery due to their characteristics of flexible locomotion or driven ability. Therefore, this paper summarizes various drug delivery microrobots developed in recent years and divides them into four categories according to different driving modes: magnetic-controlled drug delivery microrobots, anchored drug delivery microrobots, self-propelled drug delivery microrobots and biohybrid drug delivery microrobots. As oral drug delivery microrobots involve disciplines such as materials science, mechanical engineering, medicine, and control systems, this paper begins by introducing the gastrointestinal barriers that oral drug delivery must overcome. Subsequently, it provides an overview of typical materials involved in the design process of oral drug delivery microrobots. To enhance readers' understanding of the working principles and design process of oral drug delivery microrobots, we present a guideline for designing such microrobots. Furthermore, the current development status of various types of oral drug delivery microrobots is reviewed, summarizing their respective advantages and limitations. Finally, considering the significant concerns regarding safety and clinical translation, we discuss the challenges and prospections of clinical translation for various oral drug delivery microrobots presented in this paper, providing corresponding suggestions for addressing some existing challenges.

Remotely Controlled Electrochemical Degradation of Metallic Implants

Biodegradable medical implants promise to benefit patients by eliminating risks and discomfort associated with permanent implantation or surgical removal. The time until full resorption is largely determined by the implant's material composition, geometric design, and surface properties. Implants with a fixed residence time, however, cannot account for the needs of individual patients, thereby imposing limits on personalization. Here, an active Fe-based implant system is reported whose biodegradation is controlled remotely and in situ. This is achieved by incorporating a galvanic cell within the implant. An external and wireless signal is used to activate the on-board electronic circuit that controls the corrosion current between the implant body and an integrated counter electrode. This configuration leads to the accelerated degradation of the implant and allows to harvest electrochemical energy that is naturally released by corrosion. In this study, the electrochemical properties of the Fe-30Mn-1C/Pt galvanic cell model system is first investigated and high-resolution X-ray microcomputed tomography is used to evaluate the galvanic degradation of stent structures. Subsequently, a centimeter-sized active implant prototype is assembled with conventional electronic components and the remotely controlled corrosion is tested in vitro. Furthermore, strategies toward the miniaturization and full biodegradability of this system are presented.

Harnessing Disparities in Magnetic Microswarms: From Construction to Collaborative Tasks

Individual differences in size, experience, and task specialization in natural swarms often result in heterogeneity and hierarchy, facilitating efficient and coordinated task accomplishment. Drawing inspiration from this phenomenon, a general strategy is proposed for organizing magnetic micro/nanorobots (MNRs) with apparent differences in size, shape, and properties into cohesive microswarms with tunable heterogeneity, controlled spatial hierarchy, and collaborative tasking capability. In this strategy, disparate magnetic MNRs can be manipulated to show reversible transitions between synchronization and desynchronization by elaborately regulating parameter sets of the rotating magnetic field. Utilizing these transitions, alongside local robust hydrodynamic interactions, diverse heterospecific pairings of disparate magnetic MNRs can be organized into heterogeneous microswarms, and their spatial organization can be dynamically adjusted from egalitarian to leader-follower-like hierarchies on the fly, both in open space and complex microchannels. Furthermore, when specializing the disparate MNRs with distinct functions ("division of labor") such as sensing and drug carrying, they can execute precise drug delivery targeting unknown sites in a collaborative sensing-navigating-cargo dropping sequence, demonstrating significant potential for precise tumor treatment. These findings highlight the critical roles of attribute differences and hierarchical organization in designing efficient swarming micro/nanorobots for biomedical applications.

Perception of motion salience shapes the emergence of collective motions

Despite the profound implications of self-organization in animal groups for collective behaviors, understanding the fundamental principles and applying them to swarm robotics remains incomplete. Here we propose a heuristic measure of perception of motion salience (MS) to quantify relative motion changes of neighbors from first-person view. Leveraging three large bird-flocking datasets, we explore how this perception of MS relates to the structure of leader-follower (LF) relations, and further perform an individual-level correlation analysis between past perception of MS and future change rate of velocity consensus. We observe prevalence of the positive correlations in real flocks, which demonstrates that individuals will accelerate the convergence of velocity with neighbors who have higher MS. This empirical finding motivates us to introduce the concept of adaptive MS-based (AMS) interaction in swarm model. Finally, we implement AMS in a swarm of ~102 miniature robots. Swarm experiments show the significant advantage of AMS in enhancing self-organization of the swarm for smooth evacuations from confined environments.

Design and Control of the Magnetically Actuated Micro/Nanorobot Swarm toward Biomedical Applications

Recently, magnetically actuated micro/nanorobots hold extensive promises in biomedical applications due to their advantages of noninvasiveness, fuel-free operation, and programmable nature. While effectively promised in various fields such as targeted delivery, most past investigations are mainly displayed in magnetic control of individual micro/nanorobots. Facing practical medical use, the micro/nanorobots are required for the development of swarm control in a closed-loop control manner. This review outlines the recent developments in magnetic micro/nanorobot swarms, including their actuating fundamentals, designs, controls, and biomedical applications. The fundamental principles and interactions involved in the formation of magnetic micro/nanorobot swarms are discussed first. The recent advances in the design of artificial and biohybrid micro/nanorobot swarms, along with the control devices and methods used for swarm manipulation, are presented. Furthermore, biomedical applications that have the potential to achieve clinical application are introduced, such as imaging-guided therapy, targeted delivery, embolization, and biofilm eradication. By addressing the potential challenges discussed toward the end of this review, magnetic micro/nanorobot swarms hold promise for clinical treatments in the future.

Heterogeneous Sensor-Carrier Microswarms for Collaborative Precise Drug Delivery toward Unknown Targets with Localized Acidosis

Micro/nanorobots hold the potential to revolutionize biomedicine by executing diverse tasks in hard-to-reach biological environments. Nevertheless, achieving precise drug delivery to unknown disease sites using swarming micro/nanorobots remains a significant challenge. Here we develop a heterogeneous swarm comprising sensing microrobots (sensor-bots) and drug-carrying microrobots (carrier-bots) with collaborative tasking capabilities for precise drug delivery toward unknown sites. Leveraging robust interspecific hydrodynamic interactions, the sensor-bots and carrier-bots spontaneously synchronize and self-organize into stable heterogeneous microswarms. Given that the sensor-bots can create real-time pH maps employing pH-responsive structural-color changes and the doxorubicin-loaded carrier-bots exhibit selective adhesion to acidic targets via pH-responsive charge reversal, the sensor-carrier microswarm, when exploring unknown environments, can detect and localize uncharted acidic targets, guide itself to cover the area, and finally deploy therapeutic carrier-bots precisely there. This versatile platform holds promise for treating diseases with localized acidosis and inspires future theranostic microsystems with expandability, task flexibility, and high efficiency.

Magnetic Microrobot Swarms with Polymeric Hands Catching Bacteria and Microplastics in Water

The forefront of micro- and nanorobot research involves the development of smart swimming micromachines emulating the complexity of natural systems, such as the swarming and collective behaviors typically observed in animals and microorganisms, for efficient task execution. This study introduces magnetically controlled microrobots that possess polymeric sequestrant "hands" decorating a magnetic core. Under the influence of external magnetic fields, the functionalized magnetic beads dynamically self-assemble from individual microparticles into well-defined rotating planes of diverse dimensions, allowing modulation of their propulsion speed, and exhibiting a collective motion. These mobile microrobotic swarms can actively capture free-swimming bacteria and dispersed microplastics "on-the-fly", thereby cleaning aquatic environments. Unlike conventional methods, these microrobots can be collected from the complex media and can release the captured contaminants in a second vessel in a controllable manner, that is, using ultrasound, offering a sustainable solution for repeated use in decontamination processes. Additionally, the residual water is subjected to UV irradiation to eliminate any remaining bacteria, providing a comprehensive cleaning solution. In summary, this study shows a swarming microrobot design for water decontamination processes.

Magnetic Soft Microrobot Design for Cell Grasping and Transportation

Manipulating cells at a small scale is widely acknowledged as a complex and challenging task, especially when it comes to cell grasping and transportation. Various precise methods have been developed to remotely control the movement of microrobots. However, the manipulation of micro-objects necessitates the use of end-effectors. This paper presents a study on the control of movement and grasping operations of a magnetic microrobot, utilizing only 3 pairs of electromagnetic coils. A specially designed microgripper is employed on the microrobot for efficient cell grasping and transportation. To ensure precise grasping, a bending deformation model of the microgripper is formulated and subsequently validated. To achieve precise and reliable transportation of cells to specific positions, an approach that combines an extended Kalman filter with a model predictive control method is adopted to accomplish the trajectory tracking task. Through experiments, we observe that by applying the proposed control strategy, the mean absolute error of path tracking is found to be less than 0.155 mm. Remarkably, this value accounts for only 1.55% of the microrobot's size, demonstrating the efficacy and accuracy of our control strategy. Furthermore, an experiment involving the grasping and transportation of a zebrafish embryonic cell (diameter: 800 μm) is successfully conducted. The results of this experiment not only validate the precision and effectiveness of the proposed microrobot and its associated models but also highlight its tremendous potential for cell manipulation in vitro and in vivo.

Swarm Autonomy: From Agent Functionalization to Machine Intelligence

Swarm behaviors are common in nature, where individual organisms collaborate via perception, communication, and adaptation. Emulating these dynamics, large groups of active agents can self-organize through localized interactions, giving rise to complex swarm behaviors, which exhibit potential for applications across various domains. This review presents a comprehensive summary and perspective of synthetic swarms, to bridge the gap between the microscale individual agents and potential applications of synthetic swarms. It is begun by examining active agents, the fundamental units of synthetic swarms, to understand the origins of their motility and functionality in the presence of external stimuli. Then inter-agent communications and agent-environment communications that contribute to the swarm generation are summarized. Furthermore, the swarm behaviors reported to date and the emergence of machine intelligence within these behaviors are reviewed. Eventually, the applications enabled by distinct synthetic swarms are summarized. By discussing the emergent machine intelligence in swarm behaviors, insights are offered into the design and deployment of autonomous synthetic swarms for real-world applications.

Targeting biofilm infections in humans using small scale robotics

The eradication of drug-resistant microbial biofilms remains an unresolved global health challenge. Small-scale robotics are providing innovative therapeutic and diagnostic approaches with high precision and efficacy. These approaches are rapidly moving from proof-of-concept studies to translational biomedical applications using ex vivo, animal, and clinical models. Here, we discuss the fundamental and translational aspects of how microrobots target the infection sites to disrupt the structural and functional traits of biofilms and their antimicrobial resistance mechanisms. We emphasize current approaches of mechanochemical disruption and on-site drug delivery that are supported by in vivo models and preclinical testing, while also highlighting diagnostics potential. We also discuss clinical translation challenges and provide perspectives for development of microrobotics approaches to combat biofilm infections and biofouling in humans.

AcousticRobots: Smart acoustically powered micro-/nanoswimmers for precise biomedical applications

Although nanotechnology has evolutionarily progressed in biomedical field over the past decades, achieving satisfactory therapeutic effects remains difficult with limited delivery efficiency. Ultrasound could provide a deep penetration and maneuverable actuation to efficiently power micro-/nanoswimmers with little harm, offering an emerging and fascinating alternative to the active delivery platform. Recent advances in novel fabrication, controllable concepts like intelligent swarm and the integration of hybrid propulsions have promoted its function and potential for medical applications. In this review, we will summarize the mechanisms and types of ultrasonically propelled micro/nanorobots (termed here as "AcousticRobots"), including the interactions between AcousticRobots and acoustic field, practical design considerations (e.g., component, size, shape), the synthetic methods, surface modification, controllable behaviors, and the advantages when combined with other propulsion approaches. The representative biomedical applications of functional AcousticRobots are also highlighted, including drug delivery, invasive surgery, eradication on the surrounding bio-environment, cell manipulation, detection, and imaging, etc. We conclude by discussing the challenges and outlook of AcousticRobots in biomedical applications.

Self-sustainable autonomous soft actuators

Self-sustainable autonomous locomotion is a non-equilibrium phenomenon and an advanced intelligence of soft-bodied organisms that exhibit the abilities of perception, feedback, decision-making, and self-sustainment. However, artificial self-sustaining architectures are often derived from algorithms and onboard modules of soft robots, resulting in complex fabrication, limited mobility, and low sensitivity. Self-sustainable autonomous soft actuators have emerged as naturally evolving systems that do not require human intervention. With shape-morphing materials integrating in their structural design, soft actuators can direct autonomous responses to complex environmental changes and achieve robust self-sustaining motions under sustained stimulation. This perspective article discusses the recent advances in self-sustainable autonomous soft actuators. Specifically, shape-morphing materials, motion characteristics, built-in negative feedback loops, and constant stimulus response patterns used in autonomous systems are summarized. Artificial self-sustaining autonomous concepts, modes, and deformation-induced functional applications of soft actuators are described. The current challenges and future opportunities for self-sustainable actuation systems are also discussed.

Magnetic Lateral Ladder for Unidirectional Transport of Microrobots: Design Principles and Potential Applications of Cells-on-Chip

Functionalized microrobots, which are directionally manipulated in a controlled and precise manner for specific tasks, face challenges. However, magnetic field-based controls constrain all microrobots to move in a coordinated manner, limiting their functions and independent behaviors. This article presents a design principle for achieving unidirectional microrobot transport using an asymmetric magnetic texture in the shape of a lateral ladder, which the authors call the "railway track." An asymmetric magnetic energy distribution along the axis allows for the continuous movement of microrobots in a fixed direction regardless of the direction of the magnetic field rotation. The authors demonstrated precise control and simple utilization of this method. Specifically, by placing magnetic textures with different directionalities, an integrated cell/particle collector can collect microrobots distributed in a large area and move them along a complex trajectory to a predetermined location.  The authors can leverage the versatile capabilities offered by this texture concept, including hierarchical isolation, switchable collection, programmable pairing, selective drug-response test, and local fluid mixing for target objects. The results demonstrate the importance of microrobot directionality in achieving complex individual control. This novel concept represents significant advancement over conventional magnetic field-based control technology and paves the way for further research in biofunctionalized microrobotics.

AI-enhanced biomedical micro/nanorobots in microfluidics

Human beings encompass sophisticated microcirculation and microenvironments, incorporating a broad spectrum of microfluidic systems that adopt fundamental roles in orchestrating physiological mechanisms. In vitro recapitulation of human microenvironments based on lab-on-a-chip technology represents a critical paradigm to better understand the intricate mechanisms. Moreover, the advent of micro/nanorobotics provides brand new perspectives and dynamic tools for elucidating the complex process in microfluidics. Currently, artificial intelligence (AI) has endowed micro/nanorobots (MNRs) with unprecedented benefits, such as material synthesis, optimal design, fabrication, and swarm behavior. Using advanced AI algorithms, the motion control, environment perception, and swarm intelligence of MNRs in microfluidics are significantly enhanced. This emerging interdisciplinary research trend holds great potential to propel biomedical research to the forefront and make valuable contributions to human health. Herein, we initially introduce the AI algorithms integral to the development of MNRs. We briefly revisit the components, designs, and fabrication techniques adopted by robots in microfluidics with an emphasis on the application of AI. Then, we review the latest research pertinent to AI-enhanced MNRs, focusing on their motion control, sensing abilities, and intricate collective behavior in microfluidics. Furthermore, we spotlight biomedical domains that are already witnessing or will undergo game-changing evolution based on AI-enhanced MNRs. Finally, we identify the current challenges that hinder the practical use of the pioneering interdisciplinary technology.

Tracking and navigation of a microswarm under laser speckle contrast imaging for targeted delivery

Micro/nanorobotic swarms consisting of numerous tiny building blocks show great potential in biomedical applications because of their collective active delivery ability, enhanced imaging contrast, and environment-adaptive capability. However, in vivo real-time imaging and tracking of micro/nanorobotic swarms remain a challenge, considering the limited imaging size and spatial-temporal resolution of current imaging modalities. Here, we propose a strategy that enables real-time tracking and navigation of a microswarm in stagnant and flowing blood environments by using laser speckle contrast imaging (LSCI), featuring full-field imaging, high temporal-spatial resolution, and noninvasiveness. The change in dynamic convection induced by the microswarm can be quantitatively investigated by analyzing the perfusion unit (PU) distribution, offering an alternative approach to investigate the swarm behavior and its interaction with various blood environments. Both the microswarm and surrounding environment were monitored and imaged by LSCI in real time, and the images were further analyzed for simultaneous swarm tracking and navigation in the complex vascular system. Moreover, our strategy realized real-time tracking and delivery of a microswarm in vivo, showing promising potential for LSCI-guided active delivery of microswarm in the vascular system.

Embedded Physical Intelligence in Liquid Crystalline Polymer Actuators and Robots

Responsive materials possess the inherent capacity to autonomously sense and respond to various external stimuli, demonstrating physical intelligence. Among the diverse array of responsive materials, liquid crystalline polymers (LCPs) stand out for their remarkable reversible stimuli-responsive shape-morphing properties and their potential for creating soft robots. While numerous reviews have extensively detailed the progress in developing LCP-based actuators and robots, there exists a need for comprehensive summaries that elucidate the underlying principles governing actuation and how physical intelligence is embedded within these systems. This review provides a comprehensive overview of recent advancements in developing actuators and robots endowed with physical intelligence using LCPs. This review is structured around the stimulus conditions and categorizes the studies involving responsive LCPs based on the fundamental control and stimulation logic and approach. Specifically, three main categories are examined: systems that respond to changing stimuli, those operating under constant stimuli, and those equip with learning and logic control capabilities. Furthermore, the persisting challenges that need to be addressed are outlined and discuss the future avenues of research in this dynamic field.

Magnetically Manipulated Optoelectronic Hybrid Microrobots for Optically Targeted Non-Genetic Neuromodulation

Optically controlled neuromodulation is a promising approach for basic research of neural circuits and the clinical treatment of neurological diseases. However, developing a non-invasive and well-controllable system to deliver accurate and effective neural stimulation is challenging. Micro/nanorobots have shown great potential in various biomedical applications because of their precise controllability. Here, a magnetically-manipulated optoelectronic hybrid microrobot (MOHR) is presented for optically targeted non-genetic neuromodulation. By integrating the magnetic component into the metal-insulator-semiconductor junction design, the MOHR has excellent magnetic controllability and optoelectronic properties. The MOHR displays a variety of magnetic manipulation modes that enables precise and efficient navigation in different biofluids. Furthermore, the MOHR could achieve precision neuromodulation at the single-cell level because of its accurate targeting ability. This neuromodulation is achieved by the MOHR's photoelectric response to visible light irradiation, which enhances the excitability of the targeted cells. Finally, it is shown that the well-controllable MOHRs effectively restore neuronal activity in neurons damaged by β-amyloid, a pathogenic agent of Alzheimer's disease. By coupling precise controllability with efficient optoelectronic properties, the hybrid microrobot system is a promising strategy for targeted on-demand optical neuromodulation.

Ultrasound robotics for precision therapy

In recent years, the application of microrobots in precision therapy has gained significant attention. The small size and maneuverability of these micromachines enable them to potentially access regions that are difficult to reach using traditional methods; thus, reducing off-target toxicities and maximizing treatment effectiveness. Specifically, acoustic actuation has emerged as a promising method to exert control. By harnessing the power of acoustic energy, these small machines potentially navigate the body, assemble at the desired sites, and deliver therapies with enhanced precision and effectiveness. Amidst the enthusiasm surrounding these miniature agents, their translation to clinical environments has proven difficult. The primary objectives of this review are threefold: firstly, to offer an overview of the fundamental acoustic principles employed in the field of microrobots; secondly, to assess their current applications in medical therapies, encompassing tissue targeting, drug delivery or even cell infiltration; and lastly, to delve into the continuous efforts aimed at integrating acoustic microrobots into in vivo applications.

Micro/nanosystems for controllable drug delivery to the brain

Drug delivery to the brain is crucial in the treatment for central nervous system disorders. While significant progress has been made in recent years, there are still major challenges in achieving controllable drug delivery to the brain. Unmet clinical needs arise from various factors, including controlled drug transport, handling large drug doses, methods for crossing biological barriers, the use of imaging guidance, and effective models for analyzing drug delivery. Recent advances in micro/nanosystems have shown promise in addressing some of these challenges. These include the utilization of microfluidic platforms to test and validate the drug delivery process in a controlled and biomimetic setting, the development of novel micro/nanocarriers for large drug loads across the blood-brain barrier, and the implementation of micro-intervention systems for delivering drugs through intraparenchymal or peripheral routes. In this article, we present a review of the latest developments in micro/nanosystems for controllable drug delivery to the brain. We also delve into the relevant diseases, biological barriers, and conventional methods. In addition, we discuss future prospects and the development of emerging robotic micro/nanosystems equipped with directed transportation, real-time image guidance, and closed-loop control.

Complex motion of steerable vesicular robots filled with active colloidal rods

While the collective motion of active particles has been studied extensively, effective strategies to navigate particle swarms without external guidance remain elusive. We introduce a method to control the trajectories of two-dimensional swarms of active rod-like particles by confining the particles to rigid bounding membranes (vesicles) with non-uniform curvature. We show that the propelling agents spontaneously form clusters at the membrane wall and collectively propel the vesicle, turning it into an active superstructure. To further guide the motion of the superstructure, we add discontinuous features to the rigid membrane boundary in the form of a kinked tip, which acts as a steering component to direct the motion of the vesicle. We report that the system's geometrical and material properties, such as the aspect ratio and Péclet number of the active rods as well as the kink angle and flexibility of the membrane, determine the stacking of active particles close to the kinked confinement and induce a diverse set of dynamical behaviors of the superstructure, including linear and circular motion both in the direction of, and opposite to, the kink. From a systematic study of these various behaviors, we design vesicles with switchable and reversible locomotions by tuning the confinement parameters. The observed phenomena suggest a promising mechanism for particle transportation and could be used as a basic element to navigate active matter through complex and tortuous environments.

System integration of magnetic medical microrobots: from design to control

Magnetic microrobots are ideal for medical applications owing to their deep tissue penetration, precise control, and flexible movement. After decades of development, various magnetic microrobots have been used to achieve medical functions such as targeted delivery, cell manipulation, and minimally invasive surgery. This review introduces the research status and latest progress in the design and control systems of magnetic medical microrobots from a system integration perspective and summarizes the advantages and limitations of the research to provide a reference for developers. Finally, the future development direction of magnetic medical microrobot design and control systems are discussed.

Magnetic Continuum Robot with Intraoperative Magnetic Moment Programming

Magnetic continuum robots (MCRs), which are free of complicated structural designs for transmission, can be miniaturized and are therefore widely used in the medical field. However, the deformation shapes of different segments, including deflection directions and curvatures, are difficult to control simultaneously under an external programmable magnetic field. This is because the latest MCRs have designs with an invariable magnetic moment combination or profile of one or more actuating units. Therefore, the limited dexterity of the deformation shape causes the existing MCRs to collide readily with their surroundings or makes them unable to approach difficult-to-reach regions. These prolonged collisions are unnecessary or even hazardous, especially for catheters or similar medical devices. In this study, a novel magnetic moment intraoperatively programmable continuum robot (MMPCR) is introduced. By applying the proposed magnetic moment programming method, the MMPCR can deform under three modalities, that is, J, C, and S shapes. Additionally, the deflection directions and curvatures of different segments in the MMPCR can be modulated as desired. Furthermore, the magnetic moment programming and MMPCR kinematics are modeled, numerically simulated, and experimentally validated. The experimental results exhibit a mean deflection angle error of 3.3° and correspond well with simulation results. Comparisons between navigation capacities of the MMPCR and MCR demonstrate that the MMPCR has a higher capacity for dexterous deformation.

Reconfigurable self-assembly of photocatalytic magnetic microrobots for water purification

The development of artificial small-scale robotic swarms with nature-mimicking collective behaviors represents the frontier of research in robotics. While microrobot swarming under magnetic manipulation has been extensively explored, light-induced self-organization of micro- and nanorobots is still challenging. This study demonstrates the interaction-controlled, reconfigurable, reversible, and active self-assembly of TiO2/α-Fe2O3 microrobots, consisting of peanut-shaped α-Fe2O3 (hematite) microparticles synthesized by a hydrothermal method and covered with a thin layer of TiO2 by atomic layer deposition (ALD). Due to their photocatalytic and ferromagnetic properties, microrobots autonomously move in water under light irradiation, while a magnetic field precisely controls their direction. In the presence of H2O2 fuel, concentration gradients around the illuminated microrobots result in mutual attraction by phoretic interactions, inducing their spontaneous organization into self-propelled clusters. In the dark, clusters reversibly reconfigure into microchains where microrobots are aligned due to magnetic dipole-dipole interactions. Microrobots' active motion and photocatalytic properties were investigated for water remediation from pesticides, obtaining the rapid degradation of the extensively used, persistent, and hazardous herbicide 2,4-Dichlorophenoxyacetic acid (2,4D). This study potentially impacts the realization of future intelligent adaptive metamachines and the application of light-powered self-propelled micro- and nanomotors toward the degradation of persistent organic pollutants (POPs) or micro- and nanoplastics.

Optically Programmable Living Microrouter in Vivo

With high reconfigurability and swarming intelligence, programmable medical micromachines (PMMs) represent a revolution in microrobots for executing complex coordinated tasks, especially for dynamic routing of various targets along their respective routes. However, it is difficult to achieve a biocompatible implantation into the body due to their exogenous building blocks. Herein, a living microrouter based on an organic integration of endogenous red blood cells (RBCs), programmable scanning optical tweezers and flexible optofluidic strategy is reported. By harvesting energy from a designed optical force landscape, five RBCs are optically rotated in a controlled velocity and direction, under which, a specific actuation flow is achieved to exert the well-defined hydrodynamic forces on various biological targets, thus enabling a selective routing by integrating three successive functions, i.e., dynamic input, inner processing, and controlled output. Benefited from the optofluidic manipulation, various blood cells, such as the platelets and white blood cells, are transported toward the damaged vessel and cell debris for the dynamic hemostasis and targeted clearance, respectively. Moreover, the microrouter enables a precise transport of nanodrugs for active and targeted delivery in a large quantity. The proposed RBC microrouter might provide a biocompatible medical platform for cell separation, drug delivery, and immunotherapy.

Swarming Multifunctional Heater-Thermometer Nanorobots for Precise Feedback Hyperthermia Delivery

Micro-/nanorobots (MNRs) are envisioned to act as "motile-targeting" platforms for biomedical tasks due to their ability to propel and navigate in challenging, hard-to-reach biological environments. However, it remains a great challenge for current swarming MNRs to accurately report and regulate therapeutic doses during disease treatment. Here we present the development of swarming multifunctional heater-thermometer nanorobots (HT-NRs) and their application in precise feedback photothermal hyperthermia delivery. The HT-NRs are designed as photothermal-responsive photonic nanochains consisting of magnetic Fe3O4 nanoparticles arranged periodically in one dimension and encapsulated in a temperature-responsive hydrogel shell. The HT-NRs exhibit energetic and controllable swarming motions under a rotating magnetic field, while simultaneously functioning as motile nanoheaters and nanothermometers, utilizing their photothermal conversion and (photo)thermal-responsive structural color changes (photothermochromism). Consequently, the HT-NRs can be quickly deployed to a remote target area (e.g., a superficial tumor lesion) using their collective motion and selectively eliminate diseased cells in a specific targeted region by utilizing their self-reporting photothermochromism as visual feedback for precisely regulating external light irradiation. This work may inspire the development of intelligent multifunctional theranostic micro-/nanorobots and their practical applications in precise disease treatment.

Microrobots for Biomedicine: Unsolved Challenges and Opportunities for Translation

Microrobots are being explored for biomedical applications, such as drug delivery, biological cargo transport, and minimally invasive surgery. However, current efforts largely focus on proof-of-concept studies with nontranslatable materials through a "design-and-apply" approach, limiting the potential for clinical adaptation. While these proof-of-concept studies have been key to advancing microrobot technologies, we believe that the distinguishing capabilities of microrobots will be most readily brought to patient bedsides through a "design-by-problem" approach, which involves focusing on unsolved problems to inform the design of microrobots with practical capabilities. As outlined below, we propose that the clinical translation of microrobots will be accelerated by a judicious choice of target applications, improved delivery considerations, and the rational selection of translation-ready biomaterials, ultimately reducing patient burden and enhancing the efficacy of therapeutic drugs for difficult-to-treat diseases.

On-Demand Breaking of Action-Reaction Reciprocity between Magnetic Microdisks Using Global Stimuli

Coupled physical interactions induce emergent collective behaviors of many interacting objects. Nonreciprocity in the interactions generates unexpected behaviors. There is a lack of experimental model system that switches between the reciprocal and nonreciprocal regime on demand. Here, we study a system of magnetic microdisks that breaks action-reaction reciprocity via fluid-mediated hydrodynamic interactions, on demand. Via experiments and simulations, we demonstrate that nonreciprocal interactions generate self-propulsion-like behaviors of a pair of disks; group separation in collective of magnetically nonidentical disks; and decouples a part of the group from the rest. Our results could help in developing controllable microrobot collectives. Our approach highlights the effect of global stimuli in generating nonreciprocal interactions.

Microfluidic Approaches for Microactuators: From Fabrication, Actuation, to Functionalization

Microactuators can autonomously convert external energy into specific mechanical motions. With the feature sizes varying from the micrometer to millimeter scale, microactuators offer many operation and control possibilities for miniaturized devices. In recent years, advanced microfluidic techniques have revolutionized the fabrication, actuation, and functionalization of microactuators. Microfluidics can not only facilitate fabrication with continuously changing materials but also deliver various signals to stimulate the microactuators as desired, and consequently improve microfluidic chips with multiple functions. Herein, this cross-field that systematically correlates microactuator properties and microfluidic functions is comprehensively reviewed. The fabrication strategies are classified into two types according to the flow state of the microfluids: stop-flow and continuous-flow prototyping. The working mechanism of microactuators in microfluidic chips is discussed in detail. Finally, the applications of microactuator-enriched functional chips, which include tunable imaging devices, micromanipulation tools, micromotors, and microsensors, are summarized. The existing challenges and future perspectives are also discussed. It is believed that with the rapid progress of this cutting-edge field, intelligent microsystems may realize high-throughput manipulation, characterization, and analysis of tiny objects and find broad applications in various fields, such as tissue engineering, micro/nanorobotics, and analytical devices.

3D-Printed Microrobots: Translational Challenges

The science of microrobots is accelerating towards the creation of new functionalities for biomedical applications such as targeted delivery of agents, surgical procedures, tracking and imaging, and sensing. Using magnetic properties to control the motion of microrobots for these applications is emerging. Here, 3D printing methods are introduced for the fabrication of microrobots and their future perspectives are discussed to elucidate the path for enabling their clinical translation.

Accelerating the Design of Self-Guided Microrobots in Time-Varying Magnetic Fields

Mobile robots combine sensory information with mechanical actuation to move autonomously through structured environments and perform specific tasks. The miniaturization of such robots to the size of living cells is actively pursued for applications in biomedicine, materials science, and environmental sustainability. Existing microrobots based on field-driven particles rely on knowledge of the particle position and the target destination to control particle motion through fluid environments. Often, however, these external control strategies are challenged by limited information and global actuation where a common field directs multiple robots with unknown positions. In this Perspective, we discuss how time-varying magnetic fields can be used to encode the self-guided behaviors of magnetic particles conditioned on local environmental cues. Programming these behaviors is framed as a design problem: we seek to identify the design variables (e.g., particle shape, magnetization, elasticity, stimuli-response) that achieve the desired performance in a given environment. We discuss strategies for accelerating the design process using automated experiments, computational models, statistical inference, and machine learning approaches. Based on the current understanding of field-driven particle dynamics and existing capabilities for particle fabrication and actuation, we argue that self-guided microrobots with potentially transformative capabilities are close at hand.

A self-adaptive hardware with resistive switching synapses for experience-based neurocomputing

Neurobiological systems continually interact with the surrounding environment to refine their behaviour toward the best possible reward. Achieving such learning by experience is one of the main challenges of artificial intelligence, but currently it is hindered by the lack of hardware capable of plastic adaptation. Here, we propose a bio-inspired recurrent neural network, mastered by a digital system on chip with resistive-switching synaptic arrays of memory devices, which exploits homeostatic Hebbian learning for improved efficiency. All the results are discussed experimentally and theoretically, proposing a conceptual framework for benchmarking the main outcomes in terms of accuracy and resilience. To test the proposed architecture for reinforcement learning tasks, we study the autonomous exploration of continually evolving environments and verify the results for the Mars rover navigation. We also show that, compared to conventional deep learning techniques, our in-memory hardware has the potential to achieve a significant boost in speed and power-saving.

Smart micro- and nanorobots for water purification

Less than 1% of Earth's freshwater reserves is accessible. Industrialization, population growth and climate change are further exacerbating clean water shortage. Current water-remediation treatments fail to remove most pollutants completely or release toxic by-products into the environment. The use of self-propelled programmable micro- and nanoscale synthetic robots is a promising alternative way to improve water monitoring and remediation by overcoming diffusion-limited reactions and promoting interactions with target pollutants, including nano- and microplastics, persistent organic pollutants, heavy metals, oils and pathogenic microorganisms. This Review introduces the evolution of passive micro- and nanomaterials through active micro- and nanomotors and into advanced intelligent micro- and nanorobots in terms of motion ability, multifunctionality, adaptive response, swarming and mutual communication. After describing removal and degradation strategies, we present the most relevant improvements in water treatment, highlighting the design aspects necessary to improve remediation efficiency for specific contaminants. Finally, open challenges and future directions are discussed for the real-world application of smart micro- and nanorobots.

Collective Behaviors of Active Matter Learning from Natural Taxes Across Scales

Taxis orientation is common in microorganisms, and it provides feasible strategies to operate active colloids as small-scale robots. Collective taxes involve numerous units that collectively perform taxis motion, whereby the collective cooperation between individuals enables the group to perform efficiently, adaptively, and robustly. Hence, analyzing and designing collectives is crucial for developing and advancing microswarm toward practical or clinical applications. In this review, natural taxis behaviors are categorized and synthetic microrobotic collectives are discussed as bio-inspired realizations, aiming at closing the gap between taxis strategies of living creatures and those of functional active microswarms. As collective behaviors emerge within a group, the global taxis to external stimuli guides the group to conduct overall tasks, whereas the local taxis between individuals induces synchronization and global patterns. By encoding the local orientations and programming the global stimuli, various paradigms can be introduced for coordinating and controlling such collective microrobots, from the viewpoints of fundamental science and practical applications. Therefore, by discussing the key points and difficulties associated with collective taxes of different paradigms, this review potentially offers insights into mimicking natural collective behaviors and constructing intelligent microrobotic systems for on-demand control and preassigned tasks.

Gravity-resisting colloidal collectives

Self-assembly of dynamic colloidal structures along the vertical direction has been challenging because of gravity and the complexity in controlling agent-agent interactions. Here, we present a strategy that enables the self-growing of gravity-resisting colloidal collectives. By designing a unique dual-axis oscillating magnetic field, time-varying interparticle interactions are induced to assemble magnetic particles against gravity into vertical collectives, with the structures continuing to grow until reaching dynamic equilibrium. The collectives have swarm behavior and are capable of height reconfiguration and adaptive locomotion, such as moving along a tilted substrate and under nonzero fluidic flow condition, gap and obstacle crossing, and stair climbing.

Multicomponent and multifunctional integrated miniature soft robots

Miniature soft robots with elaborate structures and programmable physical properties could conduct micromanipulation with high precision as well as access confined and tortuous spaces, which promise benefits in medical tasks and environmental monitoring. To improve the functionalities and adaptability of miniature soft robots, a variety of integrated design and fabrication strategies have been proposed for the development of miniaturized soft robotic systems integrated with multicomponents and multifunctionalities. Combining the latest advancement in fabrication technologies, intelligent materials and active control methods enable these integrated robotic systems to adapt to increasingly complex application scenarios including precision medicine, intelligent electronics, and environmental and proprioceptive sensing. Herein, this review delivers an overview of various integration strategies applicable for miniature soft robotic systems, including semiconductor and microelectronic techniques, modular assembly based on self-healing and welding, modular assembly based on bonding agents, laser machining techniques, template assisted methods with modular material design, and 3D printing techniques. Emerging applications of the integrated miniature soft robots and perspectives for the future design of small-scale intelligent robots are discussed.