Microrobot Research Articles

TrinityMag: A novel magnetically actuated miniature robot manipulating system with a human-scale workspace

TrinityMag: A novel magnetically actuated miniature robot manipulating system with a human-scale workspace

A repeated jumping solution based on the bistable film structure for film-structured miniature soft robots

Abstract Miniature film-structured robots achieved remarkable locomotion performance and various applications. The integration of a jumping function could empower existing film-structured terrestrial robots to conquer complex terrains. However, current repeated jumping mechanisms for miniature soft robots are often constrained to specific materials and mechanical configurations, rendering them incompatible with film-structured robots. A solution that effectively addresses these limitations remains absent in the field. This work introduces an electrically actuated solution for repeated jumping in miniature soft robots, utilizing a bistable film structure coupled with a numerical two-rod model. The bistable film structure integrates a flexible film, polydimethylsiloxane (PDMS) linear spring, and a shape memory alloy spring to achieve repeated jumping motion through snap-through buckling. The numerical model is employed to optimize the spring parameters, tailoring the structure to the specific properties of the target robot. To demonstrate the practicality of this solution, the bistable film structure is seamlessly integrated into an existing fast-steering insect robot, which previously lacks jumping capabilities. By customizing PDMS spring design based on the robot body’s dimensions and stiffness, the prototype robot, measuring 23 × 16 × 8 mm3 in size and 120 mg in weight, demonstrates repeated jumping ability with a maximum horizontal jumping distance of 11.8 cm (5.1 body lengths), a jumping height of 3.8 cm (4.7 body heights) and a jumping frequency of 0.1 Hz. The robot traverses a 43 cm-long road with half walls and trench obstacles in 41 s. This work presents the bistable film structure’s potential as a repeated jumping solution for film-structured robots, enhancing their obstacle-crossing abilities and expanding their applicability in complex environments.

Self-Adaptive Magnetic Liquid Metal Microrobots Capable of Crossing Biological Barriers and Wireless Neuromodulation.

Magnetic liquid-bodied microrobots (MRs) possess nearly infinite shape adaptivity. However, they currently confront the risk of structure instability/crushes during shape-morphing in tiny biological environments. This article reports that magnetic liquid metal (LM) MRs (LMMRs) show high structure stability and robust magnetic maneuverability. In this protocol, Fe nanoparticles are encapsulated inside less-than-10-μm LM microdroplets by establishing interfacial chemical potential barriers, yielding LMMRs. Their robust magnetic maneuverability originates from the magnetically controlled assembly of Fe nanoparticles inside LM and distinct liquid-solid interaction. With the self-adaptive shape-recovering capabilities even after 50% deformation, LMMRs can implement vertical climbing over walls up to 400% of its body length and traverse channels with the size of its two-thirds. The in vitro and in vivo experiments have both verified the effective magneto-mechanical stimulation of LMMRs upon neurons after their shape-adaptive crossing the blood-brain barrier under a driven magnetic field. Our work provides a promising strategy for wireless therapies with MRs by safely and effectively overcoming biological barriers.

Body orientation change of neighbors leads to scale-free correlation in collective motion

Collective motion, such as milling, flocking, and collective turning, is a common and captivating phenomenon in nature, which arises in a group of many self-propelled individuals using local interaction mechanisms. Recently, vision-based mechanisms, which establish the relationship between visual inputs and motion decisions, have been applied to model and better understand the emergence of collective motion. However, previous studies often characterize the visual input as a transient Boolean-like sensory stream, which makes it challenging to capture the salient movements of neighbors. This further hinders the onset of the collective response in vision-based mechanisms and increases demands on visual sensing devices in robotic swarms. An explicit and context-related visual cue serving as the sensory input for decision-making in vision-based mechanisms is still lacking. Here, we hypothesize that body orientation change (BOC) is a significant visual cue characterizing the motion salience of neighbors, facilitating the emergence of the collective response. To test our hypothesis, we reveal the significant role of BOC during collective U-turn behaviors in fish schools by reconstructing scenes from the view of individual fish. We find that an individual with the larger BOC often takes on the leading role during U-turns. To further explore this empirical finding, we build a pairwise interaction mechanism on the basis of the BOC. Then, we conduct experiments of collective spin and collective turn with a real-time physics simulator to investigate the dynamics of information transfer in BOC-based interaction and further validate its effectiveness on 50 real miniature swarm robots. The experimental results show that BOC-based interaction not only facilitates the directional information transfer within the group but also leads to scale-free correlation within the swarm. Our study highlights the practicability of interaction governed by the neighbor’s body orientation change in swarm robotics and the effect of scale-free correlation in enhancing collective response.

A non-contact thermocapillary driving system at the gas-liquid interface

Non-contact driving technology is widely utilized in various fields due to its advantages of being non-contact, wear-free, and low noise. Thermocapillary driving is an effective approach for non-contact driving at gas-liquid interfaces. When a temperature gradient exists at the gas-liquid interface, it generates a surface tension gradient, which drives the movement of micro-objects at the interface. This research proposes a system that utilizes an array of thermoelectric coolers (TECs) as a heat source, which changes the local temperature at the gas-liquid interface and generates surface tension gradients for driving the movement of interface objects. Experimental results demonstrate that foam particles with a diameter of 0.5 mm can achieve a maximum moving speed of 2.1 mm/s. Furthermore, the system can control multiple micro-objects at the gas-liquid interface for self-assembly. We have also developed a miniature biomimetic water strider robot, this system can drive the robot to perform linear and turning movements at the gas-liquid interface. This system provides a novel approach for non-contact driving of gas-liquid interfaces.

Magnetic Field Control Using an Electromagnetic Actuation System with Combined Air‐Core and Metal‐Core Coils

Magnetic fields are widely utilized for remote control of magnetic objects, with various actuation systems developed for manipulating miniature robots in research and biomedical applications. When designing a manipulation system providing a uniform magnetic field, it is also important to consider both the accessibility of the workspace and the integration of imaging tools. This article presents an electromagnetic coil system that manipulates magnetic objects within a 3D space, enhancing the magnetic field in an upward orientation. The system includes eight metal‐core coils arranged hemispherically to ensure unimpeded access to the workspace and imaging tools, along with two air‐core coils. Easier control and repeatability of the magnetic field are achieved using two joysticks and sequential programming. The versatility of the system is demonstrated by using it to manipulate a magnetic guidewire and to guide micromagnets to various targets. Additionally, using this system, oscillating magnetic fields effectively control swarms of magnetic nanoparticles, enabling operations such as dispersion, assembly, and ribbon‐like shape formation. Furthermore, the manipulation of cell‐based microrobots (cell‐bots) showcases the system's capability to handle single and multiple cell‐bots, facilitating their collection while preserving cell viability. These experiments underscore the system's potential for fundamental biomedical research and various applications.

Design and batch fabrication of anisotropic microparticles toward small-scale robots using microfluidics: recent advances.

Small-scale robots with shape anisotropy have garnered significant scientific interest due to their enhanced mobility and precise control in recent years. Traditionally, these miniature robots are manufactured using established techniques such as molding, 3D printing, and microfabrication. However, the advent of microfluidics in recent years has emerged as a promising manufacturing technology, capitalizing on the precise and dynamic manipulation of fluids at the microscale to fabricate various complex-shaped anisotropic particles. This offers a versatile and controlled platform, enabling the efficient fabrication of small-scale robots with tailored morphologies and advanced functionalities from the microfluidic-derived anisotropic microparticles at high throughput. This review highlights the recent advances in the microfluidic fabrication of anisotropic microparticles and their potential applications in small-scale robots. In this review, the term 'small-scale robots' broadly encompasses micromotors endowed with capabilities for locomotion and manipulation. Firstly, the fundamental strategies for liquid template formation and the methodologies for generating anisotropic microparticles within the microfluidic system are briefly introduced. Subsequently, the functionality of shape-anisotropic particles in forming components for small-scale robots and actuation mechanisms are emphasized. Attention is then directed towards the diverse applications of these microparticle-derived microrobots in a variety of fields, including pollution remediation, cell microcarriers, drug delivery, and biofilm eradication. Finally, we discuss future directions for the fabrication and development of miniature robots from microfluidics, shedding light on the evolving landscape of this field.

Minimal perception: enabling autonomy in resource-constrained robots.

The rapidly increasing capabilities of autonomous mobile robots promise to make them ubiquitous in the coming decade. These robots will continue to enhance efficiency and safety in novel applications such as disaster management, environmental monitoring, bridge inspection, and agricultural inspection. To operate autonomously without constant human intervention, even in remote or hazardous areas, robots must sense, process, and interpret environmental data using only onboard sensing and computation. This capability is made possible by advancements in perception algorithms, allowing these robots to rely primarily on their perception capabilities for navigation tasks. However, tiny robot autonomy is hindered mainly by sensors, memory, and computing due to size, area, weight, and power constraints. The bottleneck in these robots lies in the real-time perception in resource-constrained robots. To enable autonomy in robots of sizes that are less than 100 mm in body length, we draw inspiration from tiny organisms such as insects and hummingbirds, known for their sophisticated perception, navigation, and survival abilities despite their minimal sensor and neural system. This work aims to provide insights into designing a compact and efficient minimal perception framework for tiny autonomous robots from higher cognitive to lower sensor levels.

Magnetic Miniature Soft Robot with Reprogrammable Drug-Dispensing Functionalities: Toward Advanced Targeted Combination Therapy.

Miniature robots are untethered actuators, which have great prospects to transform targeted drug delivery because they can potentially deliver high concentrations of medicine to the disease site(s) with minimal complications. However, existing miniature robots cannot perform advanced targeted combination therapy; majority of them can at most transport one type of drug, while those that can carry multiple drugs are unable to change their drug-dispensing sequence and dosage. Furthermore, the latter robots cannot transport more than three types of drugs, selectively dispense their drugs, maintain their mobility, or release their drugs at multiple sites. Here, a millimeter-scale soft robot is proposed, which can be actuated by alternating magnetic fields to dispense four types of drugs with reprogrammable drug-dispensing sequence and dosage (dispensing rates: 0.0992-0.231µLh-1). This robot has six degrees-of-freedom motions, and it can deliver its drugs to multiple desired sites by rolling and two-anchor crawling across unstructured environments with negligible drug leakage. Such dexterity is highly desirable and unprecedented for miniature robots with drug-dispensing capabilities. The soft robot therefore has great potential to enable advanced targeted combination therapy, where four types of drugs must be delivered to various disease sites, each with a specific sequence and dosage of drugs.

Vibration Propulsion in Untethered Insect-Scale Robots with Piezoelectric Bimorphs and 3D-Printed Legs

This research presents the development and evaluation of a miniature autonomous robot inspired by insect locomotion, capable of bidirectional movement. The robot incorporates two piezoelectric bimorph resonators, 3D-printed legs, an electronic power circuit, and a battery-operated microcontroller. Each piezoelectric motor features ceramic plates measuring 15 × 1.5 × 0.6 mm3 and weighing 0.1 g, with an optimized electrode layout. The bimorphs vibrate at two flexural modes with resonant frequencies of approximately 70 and 100 kHz. The strategic placement of the 3D-printed legs converts out-of-plane motion into effective forward or backward propulsion, depending on the vibration mode. A differential drive configuration, using the two parallel piezoelectric motors and calibrated excitation signals from the microcontroller, allows for arbitrary path navigation. The fully assembled robot measures 29 × 17 × 18 mm3 and weighs 7.4 g. The robot was tested on a glass surface, reaching a maximum speed of 70 mm/s and a rotational speed of up to 190 deg./s, with power consumption of 50 mW, a cost of transport of 10, and an estimated continuous operation time of approximately 6.7 h. The robot successfully followed pre-programmed paths, demonstrating its precise control and agility in navigating complex environments, marking a significant advancement in insect-scale autonomous robotics.

Vacuum-based and body-mounted robotic-patient interface with an integrated metasurface for MRI-guided interventions

Abstract The increased clinical relevance of image-guided procedures, particularly of interventional magnetic resonance imaging (iMRI), highlights the need for advanced devices and robotics to optimize those procedures. To enable a realistic integration of robotics into the clinical workflow, robotic-patient interfaces (RPI) are required to ensure both functionality and usability. However, current concepts have issues with patient accessibility and safety, user handling, or performing interventions on versatile body regions. This work presents a novel silicone-based RPI to flexibly mount the ’Micropositioning Robotics for Image-Guided Surgery’ (μRIGS) system on differently shaped body regions through vacuum, regulated with an electronic miniature pump. Maximum holding forces of 60N at −0.1 bar and 66N at −0.2 bar relative vacuum pressure were reached depending on the applied human body area and tensile force angles. MRI with the integrated metasurface indicated up to 200% signal enhancement, enabling improved tissue contrast within the first 20mm in depth. The multifunctional design supported the incorporation of the sterile iMRI workflow concept. This RPI enables a realistic integration of future technologies such as miniature robots, tracking markers, and instrument holders into complex interventional workflows. Further long-term studies are needed to evaluate the effects of vacuum application lasting for 1-2 hours on different skin types.

Learning automatic navigation control skills for miniature helical robots from human demonstrations

Magnetic micro-robotic technology holds immense potential for revolutionizing minimally invasive procedures, particularly in the realm of interventional medicine. The ability to effectively and precisely control micro-scale, magnetically actuated robots in real-world scenarios is important. Mastering this capability promises to elevate the precision and efficacy of medical interventions, thereby enhancing patient outcomes. Numerous methods were proposed in previous work and achieved significant progress. However, these efforts primarily focused on model-based strategies and control improvements, with little attention given to the manipulation of the surgeon. This paper presents an exploration of an imitation learning approach, leveraging extensive manual operation experiments, to replicate the task of robotic navigation in simulated vascular environments. The control strategies are directly acquired from experimental observations and encapsulated within a high-dimensional neural network, specifically a tailored variant of the Residual Network (ResNet). The robustness and effectiveness of our proposed methodology are validated through comprehensive experimentation. In automatic navigation trials, the average error spanned from 2.29 mm to 3.32 mm, leading to a mean trajectory deviation of approximately 2.92 mm. The average error rate is 31% lower than that observed in traditional model-based Proportional Integral Derivative (PID) controller (approximately 3.81 mm). In addition, the maximum error (4.87 mm) is 83% of that of the traditional method (5.85 mm). Our findings emphasize the viability and benefits of learning-based techniques in micro-robot control, paving the way for innovative control strategies in interventional surgeries applications.

Numerical model of the locomotion of oscillating ‘robots’ with frictional anisotropy on differently-structured surfaces

In engineering materials, surface anisotropy is known in certain textured patterns that appear during the manufacturing process. In biology, there are numerous examples of mechanical systems which combine anisotropic surfaces with the motion, elicited due to some actuation using muscles or stimuli-responsive materials, such as highly ordered cellulose fiber arrays of plant seeds. The systems supplemented by the muscles are rather fast actuators, because of the relatively high speed of muscle contraction, whereas the latter ones are very slow, because they generate actuation depending on the daily changes in the environmental air humidity. If the substrate has ordered surface profile, one can expect certain statistical order of potential trajectories (depending on the order of the spatial distribution of the surface asperities). If not, the expected trajectories can be statistically rather random. The same presumably holds true for the artificial miniature robots that use actuation in combination with frictional anisotropy. In order to prove this hypothesis, we developed numerical model helping us to study abovementioned cases of locomotion in 2D space on an uneven terrain. We show that at extremely long times, these systems tends to behave according to the rules of ballistic diffusion. Physically, it means that their motion tends to be associated with the “channels” of the patterned substrate. Such a motion is more or less the same as it should be in the uniform space. Such asymptotic behavior is specific for the motion in model regular potential and would be impossible on more realistic (and complex) fractal reliefs. However, one can expect that in any kind of the potential with certain symmetry (hexagonal or rhombic, for example), where it is still possible to find the ways, the motion along fixed direction during long (or even almost infinite) time intervals is possible.

Tiny batteries for tiny robots

Tiny batteries for tiny robots

Miniature Modular Reconfigurable Underwater Robot Based on Synthetic Jet.

Modular reconfigurable robots exhibit prominent advantages in the reconnaissance and exploration tasks within unstructured environments for their characteristics of high adaptability and high robustness. However, due to the limitations in locomotion mechanism and integration requirements, the modular design of miniature robots in the aquatic environment encounters significant challenges. Here, a modular strategy based on the synthetic jet principle is proposed, and a modular reconfigurable robot system is developed. Specialized bottom and side jet actuators are designed with vibration motors as excitation sources, and a motion module is developed incorporating the jet actuators to realize three-dimensional agile motion. Its linear, rotational, and ascending motion speeds reach 70.7mms-1, 3.3rads-1, and 28.7mms-1, respectively. The module integrates the power supply, communication, and control system with a small size of 48mm × 38mm × 38mm, which ensures a wireless controllable motion. Then, various configurations of the multi-module robot system are established with corresponding motion schemes, and the experiments with replaceable intermediate modules are further conducted to verify the transportation and image-capturing functions. This work demonstrates the effectiveness of synthetic jet propulsion for aquatic modular reconfigurable robot systems, and it exhibits profound potential in future underwater applications.

Unearthing the history with A‐RHex: Leveraging articulated hexapod robots for archeological pre‐exploration

AbstractThis paper aims to develop a miniature mobile robot suitable to assist archeologists in their first exploration of unknown underground tombs. Due to the rather complex and irregular terrains in the tombs and inspired by the classic RHex design, we have developed a two‐segment articulated robot (A‐RHex) with two RHex design units. The robot is compact and lightweight, with dimensions of 25 cm long, 6.5 cm wide, 7 cm high, and weighs 283 g. To assist the robot in entering the tomb, we have also designed a deployment platform that can take the robots underground through a 10‐cm exploration hole. We introduce the overall design, control, and communication methods of A‐RHex, and theoretically analyze how the articulated design can improve the stability of the robot on slopes. Laboratory experiments and field testings at two real archeological excavation sites in China have validated A‐RHex's mechanical design, control strategies, communications, and capabilities for pre‐exploration of open and closed tombs. We believe that this kind of robot with high terrain adaptability and a small profile may become an important tool for field archeology in the future.

Development of hydrogen peroxide based micro thruster utilizing biomass-based catalyst bed

Micro thrusters, also referred to as micro-newton thrusters, are thrusters having a wide range of force capabilities in the micro-newton range. Micro thrusters are used in CubeSats, tiny robots and drones, micro- and nanosatellites, spacecraft attitude control, etc. The aim of the present study is to develop a monopropellant thruster (MPT) for 90 % concentrated hydrogen peroxide (H2O2). A rotatory evaporator was used to obtain a 90 % H2O2 form the available concentration of 50 % H2O2. The next stage involved the designing of the monopropellant thruster utilizing the NASA CEA rocket performance algorithm and the derived mathematical model. The test facility was constructed which includes a thruster, a feed line system, a static test firing platform, a data collecting system and the measuring sensors. To measure the thrust of the thruster, a pendulum thrust mechanism was constructed and fabricated into an experimental test stand. Lastly, the MPT chamber, which uses stainless steel mesh, was prepared and packed with the biomass-based catalyst. The 14 bar injection pressure conditions were used for the fire tests. With a mass flow rate of 5 g/s and a decomposition pressure of 10 bar, the theoretical specific impulse (Isp) was calculated to be 1993.2 Ns/kg at an O/F ratio of 0.002. The test firing with 90 % concentrated hydrogen peroxide gave an experimental specific impulse of 794.5 Ns/kg, which gives efficiency of 39.9 %.

Spatial Localization of Transformer Inspection Robot Based on Adaptive Denoising and SCOT-β Generalized Cross-Correlation.

In the detection process of the internal defects of large oil-immersed transformers, due to the huge size of large transformers and metal-enclosed structures, the positional localization of miniature inspection robots inside the transformer faces great difficulties. To address this problem, this paper proposes a three-dimensional positional localization method based on adaptive denoising and the SCOT weighting function with the addition of the exponent β (SCOT-β) generalized cross-correlation for L-type ultrasonic arrays of transformer internal inspection robots. Aiming at the strong noise interference in the field, the original signal is decomposed by an improved Empirical Mode Decomposition (EMD) method, and the optimal center frequency and bandwidth of each mode are adaptively searched. By extracting the modes in the frequency band of the positional localization signal, suppressing the modes in the noise frequency band, and reconstructing the Intrinsic Mode Function (IMF) of the independently selected superior modal components, a signal with a high signal-to-noise ratio is obtained. In addition, for the traditional mutual correlation algorithm with a large delay estimation error at a low signal-to-noise ratio, this paper adopts an improved generalized joint weighting function, SCOT-β, which improves the anti-jamming ability of the generalized mutual correlation method at a low signal-to-noise ratio by adding an exponential function to the denominator term of the SCOT weighting function's generalized cross-correlation. Finally, the accurate positional localization of the transformer internal inspection robot is realized based on the quadratic L-array and search-based maximum likelihood estimation method. Simulation and experimental results show the following: the improved EMD denoising method better improves the signal-to-noise ratio of the positional localization signal with a lower distortion rate; in the transformer test tank, which is 120 cm in length, 100 cm in width, and 100 cm in height, based on the positional localization method in this paper, the average relative positional localization error of the transformer internal inspection robot in three-dimensional space is 2.27%, and the maximum positional localization error is less than 2 cm, which meets the requirements of engineering positional localization.

Individual and collective manipulation of multifunctional bimodal droplets in three dimensions.

Spatiotemporally controllable droplet manipulation is vital across numerous applications, particularly in miniature droplet robots known for their exceptional deformability. Despite notable advancements, current droplet control methods are predominantly limited to two-dimensional (2D) deformation and motion of an individual droplet, with minimal exploration of 3D manipulation and collective droplet behaviors. Here, we introduce a bimodal actuation strategy, merging magnetic and optical fields, for remote and programmable 3D guidance of individual ferrofluidic droplets and droplet collectives. The magnetic field induces a magnetic dipole force, prompting the formation of droplet collectives. Simultaneously, the optical field triggers isothermal changes in interfacial tension through Marangoni flows, enhancing buoyancy and facilitating 3D movements of individual and collective droplets. Moreover, these droplets can function autonomously as soft robots, capable of transporting objects. Alternatively, when combined with a hydrogel shell, they assemble into jellyfish-like robots, driven by sunlight. These findings present an efficient strategy for droplet manipulation, broadening the capabilities of droplet-based robotics.

Visual route following for tiny autonomous robots.

Navigation is an essential capability for autonomous robots. In particular, visual navigation has been a major research topic in robotics because cameras are lightweight, power-efficient sensors that provide rich information on the environment. However, the main challenge of visual navigation is that it requires substantial computational power and memory for visual processing and storage of the results. As of yet, this has precluded its use on small, extremely resource-constrained robots such as lightweight drones. Inspired by the parsimony of natural intelligence, we propose an insect-inspired approach toward visual navigation that is specifically aimed at extremely resource-restricted robots. It is a route-following approach in which a robot's outbound trajectory is stored as a collection of highly compressed panoramic images together with their spatial relationships as measured with odometry. During the inbound journey, the robot uses a combination of odometry and visual homing to return to the stored locations, with visual homing preventing the buildup of odometric drift. A main advancement of the proposed strategy is that the number of stored compressed images is minimized by spacing them apart as far as the accuracy of odometry allows. To demonstrate the suitability for small systems, we implemented the strategy on a tiny 56-gram drone. The drone could successfully follow routes up to 100 meters with a trajectory representation that consumed less than 20 bytes per meter. The presented method forms a substantial step toward the autonomous visual navigation of tiny robots, facilitating their more widespread application.