Microrobot Research Articles

Microrobots for Targeted Delivery and Therapy in Digestive System.

Untethered miniature robots enable targeted delivery and therapy deep inside the gastrointestinal tract in a minimally invasive manner. By combining actuation systems and imaging tools, significant progress has been made toward the development of functional microrobots. These robots can be actuated by external fields and fuels while featuring real-time tracking feedback toward certain regions and can perform the therapeutic process by rational exertion of the local environment of the gastrointestinal tract (e.g., pH, enzyme). Compared with conventional surgical tools, such as endoscopic devices and catheters, miniature robots feature minimally invasive diagnosis and treatment, multifunctionality, high safety and adaptivity, embodied intelligence, and easy access to tortuous and narrow lumens. In addition, the active motion of microrobots enhances local penetration and retention of drugs in tissues compared to common passive oral drug delivery. Based on the dissimilar microenvironments in the various sections of the gastrointestinal tract, this review introduces the advances of miniature robots for minimally invasive targeted delivery and therapy of diseases along the gastrointestinal tract. The imaging modalities for the tracking and their application scenarios are also discussed. We finally evaluate the challenges and barriers that retard their applications and hint on future research directions in this field.

A Novel Magnetic Transmission for Powerful Miniature Surgical Robots

Untethered magnetically actuated robots present significant advantages for biomedical applications by allowing power to be delivered wirelessly to remote, miniature robots through flesh and bone. Nevertheless, generating enough usable force to interact with their environment remains a challenge: Most millimeter-size magnetic robots achieve forces of much less than 0.1 N, which limits their medical applications. Therefore, a compact, millimeter-scale transmission is needed to amplify the output force. A novel microtransmission system is presented, composed of a driving magnet suspended between two twisted string actuators. An analytical model of the transmission is formulated to predict its behavior under both fixed load and fixed displacement configurations. Experimental measurements are used to validate the predicted maximum achievable force, to quantify the transmission performance over numerous cycles, to determine the effect of different string materials, and to determine the impact of hysteresis and viscoelasticity. Finally, the transmission is integrated into a 3 mm diameter surgical gripper prototype to demonstrate its effectiveness. With only a modest 20 mT of applied magnetic field, the gripper generates 1.09 N gripping force—a factor of 35 improvement in mechanical advantage and a factor of 62 improvement in gripping force compared to a similar size gripper using direct magnetic actuation. This microtransmission for miniature magnetic robots will enable high-strength untethered robots for minimally invasive surgical applications.

SimoBot: An Underactuated Miniature Robot Driven by a Single Motor

A simple-structured, low-cost miniature robot is highly desired for swarm robotics research. In this article, we designed an underactuated miniature robot using only one motor, named as SimoBot, to save space, cost, weight, and energy consumption. Since it has only one motor but needs to travel on the 2-D ground, the design, moving mechanism, and control are all challenging. We conceived a movement strategy based on the interplaying between the centrifugal force and swinging motion of the robot to generate translation and rotation on the ground and finally follow various arbitrary paths. This robot has only five simple components—a vibration motor, a button cell, a microcontroller board, four-pin legs (one of which is shorter than the others), and sensors. This article built the kinematics and kinetics models and analyzed and optimized the parameters. The prototype weighs only 4.76 g, costs 4.7 dollars, and is 20 mm in diameter and 18 mm in height. It can run as fast as 40 mm/s. Its cost of transportation is only 55, smaller than most miniature robots with onboard power and insects. By modulating voltage polarities on the motor and the periods, we demonstrated the controllability of SimoBot by the movement along a straight line, a circle, an “S” curve, and more arbitrary trajectories.

A Small-Scale, Rat-Inspired Whisker Sensor for the Perception of a Biomimetic Robot: Design, Fabrication, Modeling, and Experimental Characterization

In this article, we present a rat-inspired whisker sensor for a biomimetic robotic rat and demonstrate its superior tactile perception performance. In particular, the design, fabrication, modeling, and experimental characterization are presented. The sensor is fabricated using silicon-on-insulator (SOI) technology. Moreover, by modeling the whisker as a Euler–Bernoulli beam (EBB) using a support vector machine (SVM) algorithm, we develop the sensor’s capability to identify object features. An experimental evaluation demonstrates the sensor’s outstanding texture discrimination ability (with an accuracy of 88.3%) and excellent performance on contour reconstruction [with a 97.14% goodness of fit (GOF)]. In addition, by realizing the robotic rat’s wall-following motion using the whisker sensor, many more features of a wall can be obtained with high accuracy. As a result, this work is, to the best of our knowledge, the first to achieve experimental progress in using a whisker sensor to control a small-scale robot on the order of a few tens of centimeters. Moreover, the whisker sensor extends this off-the-shelf SOI technology from micro to macro environments, giving it the potential for use in other miniature robots for tactile perception.

Bio-Inspired Micro- and Nanorobotics Driven by Magnetic Field.

In recent years, there has been explosive growth in the number of investigations devoted to the development and study of biomimetic micro- and nanorobots. The present review is dedicated to novel bioinspired magnetic micro- and nanodevices that can be remotely controlled by an external magnetic field. This approach to actuate micro- and nanorobots is non-invasive and absolutely harmless for living organisms in vivo and cell microsurgery, and is very promising for medicine in the near future. Particular attention has been paid to the latest advances in the rapidly developing field of designing polymer-based flexible and rigid magnetic composites and fabricating structures inspired by living micro-objects and organisms. The physical principles underlying the functioning of hybrid bio-inspired magnetic miniature robots, sensors, and actuators are considered in this review, and key practical applications and challenges are analyzed as well.

Design and adaptive control of a kinematically redundant robot with enhanced trajectory tracking for climbing in tight spaces

This work investigates the design and adaptive control of a miniature robot with multi-modal locomotion which has the ability to climb inside train bogies for inspection purposes. We propose and analyse a kinematically redundant mechanism with six 2-DOF couple joints. The robot can squeeze through narrow spaces and also climb on surfaces with transitions, irregularities and discontinuities. The unique design allows desirable self-motion close to obstacles but imposes strict requirements in motion control and precise path following. This paper applies such redundancy and self-motion by constructing an adaptive controller with time-varying safety constraints for all twelve joints of the mechanism. The control strategy relies on the time-varying Barrier Lyapunov Function to bound the trajectory error. It also deploys an adaptive radial basis function neural network to estimate the system parameters of the robot. Various simulation experiments show that the proposed controller satisfies all safety and physical joint constraints. It also minimises trajectory tracking error irrespective of initial conditions, disturbances, and unmodelled dynamic effects. Finally, we compare the tracking results with those obtained by a Feedback Linearisation controller and a Quadratic Lyapunov Function-based controller. Results demonstrate enhanced locomotion and trajectory tracking for collision-free manoeuvring in tight spaces. • A novel miniature wall-climbing robot for inspection in the rolling stock industry. • The proposed robot is bipedal with multi-modal locomotion. • The couple joints have been utilised to reach a compact and tiny design. • Intelligent time-varying-barrier-Lyapunov-based controller for wall-climbing robot. • A safe and collision motion planning in the tight space.

Collision-Free Motion Algorithms for Sensors Automated Deployment to Enable a Smart Environmental Sensing-Net

As natural habitats protection has become a global priority, smart sensing-nets are ever-increasingly needed for effective environmental observation. In a practical monitoring network, it is critical to deploy sensors with sufficient automated intelligence and motion flexibility. Recent advances in robotics and sensors technology have enabled automated mobile sensors deployment in a smart sensing-net. Existing deployment algorithms can be employed to calculate adequate destinations (goals) for sensors to perform respective monitoring tasks. However, given the calculated goal positions, the problem of how to actually coordinate a fleet of robots and schedule moving paths from random initials to reach their goals safely, without collisions, remains largely unaddressed in the wireless sensor networking (WSN) literature. In this paper, we investigate this problem and propose polynomial-time collision-free motion algorithms based on batched movements to ensure all the mobile sensors reach their goals successfully without incurring collisions. We observe that the grouping (batching) strategy is similar to the coloring procedure in graph theory. By constructing a conflict graph, we model the collision-free path scheduling as the well-known k-coloring problem, from which we reduce to our k-batching problem (determining the minimum number of required batches for a successful deployment) and prove its NP completeness. Since the k-batching problem is intractable, we develop CFMA (collision-free motion algorithm), a simple yet effective batching (coloring) heuristic mechanism, to approximate the optimal solution. Performance results show that our motion algorithms outperform other existing path-scheduling mechanisms by producing 100% sensors reachability (success probability of goals reaching), time-bounded deployment latency with low computation complexity, and reduced energy consumption. Note to Practitioners— This research was originally motivated by an oceanography project, which studied marine microbes by sending a team of tiny robots (sensors) randomly scattered on the ocean floor. For hard-to-access habitats like deserts or oceans, where manual placement of sensors is costly or impossible, automatically scheduling robots movements to calculated positions from random initials is essential for an effective monitoring. Our contribution is unique in two ways. First, traditional path-planning research focuses more on independent robots navigating the environment, whereas we target on the network automation problem, coordinating a fleet of robots working together to perform an environmental sensing task. Second, we observe that existing movement methods are too complicated and energy-consuming due to the calculation on-the-go nature. To provide a practical solution, we suggest and design our motion algorithms from a new perspective: pre-scheduled batched movements. Our approach requires a central server for grouping (batching) calculations, but can effectively reduce computation complexity and save significant energy expenditure exerted on resource-limited sensors. The proposed collision-free motion algorithm (CFMA) is a suboptimal yet efficient batching solution, which can be easily applied in real-life open-space monitoring networks. Insights from this foundational research will facilitate future opportunities to implement and verify our method in operational monitoring testbeds.

Design and Fabrication of Soft 3D Printed Sensors and Performance Analysis of the Soft Sensors in a C-leg as Sensing Element

In soft robotics, a recent challenge is to decrease the number of rigid components used tocreate entirely soft robots. A common rigid component used in soft robots is the rigid encoder, which should be replaced with a soft counterpart if possible. In this work, we de-sign and manufacture a soft sensor, which is embedded into a C-shaped leg of a soft, legged, miniature robot. Our main goal is to show that we can embed a soft sensor into and receive contact feedback from a soft C-shaped leg of our soft miniature quadruped. We test various sensor parameters using custom test setups to analyze the soft sensor performance. Our soft sensor design is iterated by experimentally investigating several sensor shape options. For the C-leg of the soft miniature quadruped, optimal sensor geometry and position for the sensor implementation are found from a discrete design space as the outcome of this work. We received feedback from the soft sensor and compared commercial encoder data to the soft sensor embedded C-leg data. We managed to detect the rotation speed of the C-leg with the accuracy of 87.5% on a treadmill and with the accuracy of %86.7 under free rotation of the C-leg. However, if connection loss occurs in the miniature slipring mechanism, the error percentage in estimating the rotational speed increases significantly.

Path Tracking and Connection Mechanism of a Reconfigurable, Foldable, Legged, and Miniature Robot

This work introduces the reconfigurable, foldable, legged, and miniature robot (REMIRO), a palm-size modular robot with compliant c-shaped legs. The robot’s body modules are made by folding acetate sheets. The legs connected to these modules are made of Polydimethylsiloxane (PDMS) using molding. The backbone modules are made of Thermoplastic polyurethane (TPU) using 3D printing. In this study, we propose a path tracking algorithm for our robot that enables our modules to move from a random initial location to the pose required to lock with another module. We also design and manufacture backbones with embedded permanent magnets to allow connection between modules. We also present a kinematic model of our robot utilizing c-shaped leg kinematics, predicting the forward differential kinematics of the robot, which is then used to test the path tracking algorithm. Our experiments show that the proposed path tracking algorithm moves our robot to the desired location with an average positioning error of 5mm and an average orientation error of 22°, which are small enough to permit docking between modules.

Motion Analysis and Real‐Time Trajectory Prediction of Magnetically Steerable Catalytic Janus Micromotors

Chemically driven micromotors display unpredictable trajectories due to the rotational Brownian motion interacting with the surrounding fluid molecules. This hampers the practical applications of these tiny robots, particularly where precise control is a requisite. To overcome the rotational Brownian motion and increase motion directionality, robots are often decorated with a magnetic composition and guided by an external magnetic field. However, despite the straightforward method, explicit analysis and modeling of their motion have been limited. Here, catalytic Janus micromotors are fabricated with distinct magnetizations and a controlled self‐propelled motion with magnetic steering is shown. To analyze their dynamic behavior, a dynamic model that can successfully predict the trajectory of micromotors in uniform viscous flows in real time by incorporating a form of state‐dependent‐coefficient with a robust two‐stage Kalman filter is theoretically developed. A good agreement is observed between the theoretically predicted dynamics and experimental observations over a wide range of model parameter variations. The developed model can be universally adopted to various designs of catalytic micro‐/nanomotors with different sizes, geometries, and materials, even in diverse fuel solutions. Finally, the proposed model can be used as a platform for biosensing, detecting fuel concentration, or determining small‐scale motors’ propulsion mechanisms in an unknown environment.

Scale-reconfigurable miniature ferrofluidic robots for negotiating sharply variable spaces.

Magnetic miniature soft robots have shown great potential for facilitating biomedical applications by minimizing invasiveness and possible physical damage. However, researchers have mainly focused on fixed-size robots, with their active locomotion accessible only when the cross-sectional dimension of these confined spaces is comparable to that of the robot. Here, we realize the scale-reconfigurable miniature ferrofluidic robots (SMFRs) based on ferrofluid droplets and propose a series of control strategies for reconfiguring SMFR’s scale and deformation to achieve trans-scale motion control by designing a multiscale magnetic miniature robot actuation (M3RA) system. The results showed that SMFRs, varying from centimeters to a few micrometers, leveraged diverse capabilities, such as locomotion in structured environments, deformation to squeeze through gaps, and even reversible scale reconfiguration for navigating sharply variable spaces. A miniature robot system with these capabilities combined is promising to be applied in future wireless medical robots inside confined regions of the human body.

Liquid Metal-Elastomer Composites with Dual-Energy Transmission Mode for Multifunctional Miniature Untethered Magnetic Robots.

Miniature untethered robots attract growing interest as they have become more functional and applicable to disruptive biomedical applications recently. Particularly, the soft ones among them exhibit unique merits of compliance, versatility, and agility. With scarce onboard space, these devices mostly harvest energy from environment or physical fields, such as magnetic and acoustic fields and patterned lights. In most cases, one device only utilizes one energy transmission mode (ETM) in powering its activities to achieve programmed tasks, such as locomotion and object manipulation. But real-world tasks demand multifunctional devices that require more energy in various forms. This work reports a liquid metal-elastomer composite with dual-ETM using one magnetic field for miniature untethered multifunctional robots. The first ETM uses the low-frequency (<100Hz) field component to induce shape-morphing, while the second ETM employs energy transmitted via radio-frequency (20kHz-300GHz) induction to power onboard electronics and generate excess heat, enabling new capabilities. These new functions do not disturb the shape-morphing actuated using the first ETM. The reported material enables the integration of electric and thermal functionalities into soft miniature robots, offering a wealth of inspirations for multifunctional miniature robots that leverage developments in electronics to exhibit usefulness beyond self-locomotion.

Integration of body-mounted ultrasoft organic solar cell on cyborg insects with intact mobility

Cyborg insects have been proposed for applications such as urban search and rescue. Body-mounted energy-harvesting devices are critical for expanding the range of activity and functionality of cyborg insects. However, their power outputs are limited to less than 1 mW, which is considerably lower than those required for wireless locomotion control. The area and load of the energy harvesting device considerably impair the mobility of tiny robots. Here, we describe the integration of an ultrasoft organic solar cell module on cyborg insects that preserves their motion abilities. Our quantified system design strategy, developed using a combination of ultrathin film electronics and an adhesive–nonadhesive interleaving structure to perform basic insect motion, successfully achieved the fundamental locomotion of traversing and self-righting. The body-mounted ultrathin organic solar cell module achieves a power output of 17.2 mW. We demonstrate its feasibility by displaying the recharging wireless locomotion control of cyborg insects.

Leveraging robotics, artificial intelligence, and machine learning for enhanced disease diagnosis and treatment: Advanced integrative approaches for precision medicine

The ever-growing burden of disease necessitates a paradigm shift in healthcare towards a more precise and data-driven approach. This paper delves into the transformative potential of integrating robotics, artificial intelligence (AI), and machine learning (ML) to revolutionize disease diagnosis and treatment. We explore advanced integrative approaches that synergistically combine robotic automation, AI-powered diagnostic tools, and ML-based predictive models to usher in the era of precision medicine. The realm of robotic systems for surgical intervention is experiencing a significant renaissance. We discuss the development and application of next-generation robotic surgical platforms. These platforms boast enhanced dexterity, improved visualization through high-definition 3D cameras, and tremor filtration capabilities, leading to minimally invasive procedures with superior precision, reduced blood loss, and faster patient recovery. We delve into the integration of haptic feedback technology that allows surgeons to experience realistic tissue manipulation, further enhancing surgical control and decision-making. Additionally, the paper explores the burgeoning field of robotic-assisted microsurgery, where miniature robots provide unparalleled access and manipulation at the cellular level, paving the way for groundbreaking advancements in areas like neurosurgery and ophthalmology. Artificial intelligence (AI) is rapidly transforming the landscape of disease diagnosis. We investigate the application of AI algorithms, particularly deep learning architectures like convolutional neural networks (CNNs), in analysing medical images for Computer-Aided Diagnosis (CAD). These algorithms, trained on vast datasets of medical scans, can achieve near-human or even superhuman levels of accuracy in identifying subtle anomalies and disease signatures within radiology images, mammograms, and pathology slides. We discuss the potential of AI-powered CAD systems to support radiologists in early disease detection, improve diagnostic accuracy, and streamline workflow efficiency. Furthermore, the paper explores the promise of AI-driven natural language processing (NLP) for analysing electronic health records (EHRs) to uncover hidden patterns and identify patients at high risk for specific diseases. This allows for proactive intervention and preventative measures tailored to individual patient needs. Machine learning (ML) plays a pivotal role in enabling personalized treatment plans. We delve into the development of robust ML models that leverage large-scale, heterogeneous healthcare datasets. These datasets encompass patient demographics, medical history, genetic information, treatment response data, and real-world clinical outcomes. By analysing such complex datasets, ML algorithms can uncover intricate relationships between patient characteristics, disease progression, and treatment efficacy. This empowers clinicians to generate personalized treatment plans that optimize therapeutic response and minimize side effects. We also discuss the potential of ML for predicting patient response to specific medications and therapies, allowing for the implementation of stratified medicine approaches. This ensures that patients receive the most effective treatment based on their unique biological makeup and disease profile. The paper underscores the importance of real-world applications and case studies in validating the transformative potential of this integrated approach. We present case studies demonstrating the successful utilization of robotic surgery in complex oncological procedures, leading to improved patient outcomes and reduced healthcare costs. Additionally, we showcase the efficacy of AI-powered CAD systems in detecting early-stage cancers, enabling timely intervention and potentially life-saving outcomes. We emphasize the need for robust data collection and standardized protocols to ensure the generalizability and scalability of these novel technologies. The impact of this integrative approach on patient outcomes and healthcare efficiency is meticulously examined. We highlight the potential for robotic surgery to minimize surgical complications, reduce hospitalization times, and improve patient recovery rates. Additionally, AI-powered diagnostic tools can facilitate faster and more accurate diagnoses, enabling earlier intervention and potentially leading to better long-term health outcomes for patients. Furthermore, ML-driven predictive models promote personalized treatments, potentially leading to improved treatment efficacy and cost savings through reduced unnecessary interventions. This paper comprehensively analyses the transformative potential of integrating robotics, AI, and ML to revolutionize disease diagnosis and treatment. By leveraging these advanced technologies, we can usher in a new era of precision medicine, characterized by personalized treatment plans, improved patient outcomes, and enhanced healthcare efficiency. However, this paradigm shift necessitates addressing challenges like data privacy, regulatory frameworks, and equitable access to these technologies. By fostering interdisciplinary collaboration between engineers, clinicians, and data scientists, we can ensure the responsible and ethical development of these powerful tools, ultimately paving the way for a healthier future for all.

Miniature Amphibious Robot Actuated by Rigid-Flexible Hybrid Vibration Modules.

Amphibious robots can undertake various tasks in terrestrial and aquatic environments for their superior environmental compatibility. However, the existing amphibious robots usually utilize multi‐locomotion systems with transmission mechanisms, leading to complex and bulky structures. Here, a miniature amphibious robot based on vibration‐driven locomotion mechanism is developed. The robot has two unique rigid‐flexible hybrid modules (RFH‐modules), in which a soft foot and a flexible fin are arranged on a rigid leg to conduct vibrations from an eccentric motor to the environment. Then, it can run on ground with the soft foot adopting the friction locomotion mechanism and swim on water with the flexible fin utilizing the vibration‐induced flow mechanism. The robot is untethered with a compact size of 75 × 95 × 21 mm3 and a small weight of 35 g owing to no transmission mechanism or joints. It realizes the maximum speed of 815 mm s–1 on ground and 171 mm s–1 on water. The robot, actuated by the RFH‐modules based on vibration‐driven locomotion mechanism, exhibits the merits of miniature structure and fast movements, indicating its great potential for applications in narrow amphibious environments.

On-demand anchoring of wireless soft miniature robots on soft surfaces

Untethered soft miniature robots capable of accessing hard-to-reach regions can enable new, disruptive, and minimally invasive medical procedures. However, once the control input is removed, these robots easily move from their target location because of the dynamic motion of body tissues or fluids, thereby restricting their use in many long-term medical applications. To overcome this, we propose a wireless spring-preloaded barbed needle release mechanism, which can provide up to 1.6 N of force to drive a barbed needle into soft tissues to allow robust on-demand anchoring on three-dimensional (3D) surfaces. The mechanism is wirelessly triggered using radio-frequency remote heating and can be easily integrated into existing untethered soft robotic platforms without sacrificing their mobility. Design guidelines aimed at maximizing anchoring over the range of the most biological tissues (kPa range) and extending the operating depth of the device inside the body (up to 75%) are also presented. Enabled by these advances, we achieve robust anchoring on a variety of ex vivo tissues and demonstrate the usage of such a device when integrated with existing soft robotic platforms and medical imaging. Moreover, by simply changing the needle, we demonstrate additional functionalities such as controlled detachment and subsurface drug delivery into 3D cancer spheroids. Given these capabilities, our proposed mechanism could enable the development of a new class of biomedical-related functionalities, such as local drug delivery, disease monitoring, and hyperthermia for future untethered soft medical robots.

Miniature Mobile Robot Using Only One Tilted Vibration Motor.

In miniature mobile robots, reducing the number of actuators can effectively reduce the size and weight of the robot. However, it is challenging to design a robot with as few actuators as possible without losing good motion performance. This work presented a simple-structured low-cost miniature mobile robot. It is driven by only a single tilted motor and yet is fully capable of being controlled to move forward and turn left or right on the ground. Based on the stick–slip mechanism, the robot’s motion is achieved by interplaying between the centrifugal force generated by the vibration motor tilted on the robot and the friction force of the robot. The robot’s speed can be controlled by regulating the magnitude and the period of the applied voltage. Finally, the robot can translate and rotate on the ground and follow various arbitrary paths. The prototype weighs only 11.15 g, costs $6.35, and is 20 mm in diameter and 25 mm in height. The proposed system is experimentally verified and demonstrates the controllability of the robot by the movement along a straight line, a circle, and more arbitrary paths.

Real-Time Navigation of an Untethered Miniature Robot Using Mobile Ultrasound Imaging and Magnetic Actuation Systems

Remotely actuated small-scale robots have shown promising capabilities in targeted delivery, micromanipulation, and biosensing. However, challenges remain in imaging and control of a robot in a large workspace, especially when conducting targeted navigation in hard-to-reach and tortuous regions of a living body. In this work, we propose a strategy for real-time magnetic navigation of an untethered miniature robot in a large workspace using ultrasound image feedback. A mobile electromagnetic coil-based system is designed to control and simultaneously track the robot in a large working space. An ultrasound probe is integrated with a three degree-of-freedom (DoF) manipulator to sweep the workspace and actively follow the miniature robot, where a dynamic region of interest (ROI) is applied to track the robot in real-time. Experiments in two tissue-mimicking phantoms with branching and tortuous environments are respectively conducted. Results demonstrate that the robot can selectively navigate along different paths of the branching environment, and it also exhibits long-distance navigation in a tortuous environment. The mean transverse deviations between the planned trajectory and tracking position are less than the radius of the tube, and the mean tracking intervals are less than half body length of the robot. These results validate the feasibility of the mobile ultrasound-integrated navigation strategy, demonstrating a potential approach for navigating a miniature robot inside hard-to-reach regions under medical imaging guidance.

Comparative Study to Analyze MEMS Based Microrobot Using Fuzzy TOPSIS Approach

With the emergence in the field of developing small-scale systems, microrobots are gaining enormous attention due to their small size, wide number of application, and negligible effects on the surrounding. MEMS and microrobots both have electrical and mechanical parts which are situated on a single device and chip. This makes MEMS based microrobots and an excellent device due to its ease of fabrication and small size. MEMS-based microrobots have a wide number of applications in the field of bio-medical special drug delivery and invasive surgery. These tiny robots can be sent into the human body to send any medicine inside the human body. Various types of MEMS based microrobot can be used in drug delivery applications including magnetic nanoparticles based microrobots, magnetized spirulina microrobot, and electro-magnetic microrobots. However, the suitability of all these robots for drug delivery applications depends on the locomotion, navigation controlling, shape transformation, actuation requirement, and amount of drug wasted before moving to the destination. In this work, fuzzy rules based system is performed to confirm the dependence of the parameters including the locomotion, navigation controlling, shape transformation, actuation requirement, and amount of drug wasted on the working of microrobots in drug delivery applications. Similarly, fuzzy TOPSIS based study is performed to compare and analyze the most suitable microrobot for drug delivery application. Piezo-electric and electro-magnetic microrobots are considered the most suitable option with relative closeness to the ideal solution of 0.71 and 0.66, respectively, owing to their better shape transformation and movement.

NANOPARTICLES IN EMERGING PARENTERAL DRUG THERAPY: AN OVERVIEW

Aim: The aim of the study was to discuss the recent researches done over the nanoparticles and types of nanoparticles being useful in the parenteral delivery of drugs. Materials and methods: Different types of nanoparticles are developed i.e., liposomes, polymeric nanoparticles, nano-capsules, dendrimers, nanotubes, nanowires, nanocrystals and nanobots. Nanoparticles are very beneficial in pharmacy and health sciences as in cancer therapy, biological binders, drug carriers, targeted therapy etc. to boost the healthcare system. It aids in the improvement of medication solubility and bioavailability, as well as the reduction of toxicity, improved release, and better formulation options. It's worth noting that various commercial oral medications have been created using nanoparticle technology to improve API absorption. Nano-milling process is used to increase absorption of nano-parenteral. Conclusion: Active targeting is useful in oncology, especially for the treatment of malignancies, because it can reduce side effects. Consider tiny miniature robots that your doctor will inject into vein to look for cancer cells or administer a medicine. We anticipate that this system will modify cancer immunotherapy and provide novel therapeutic options in the near future. Keywords: Nanoparticles, Nanowires, Nano-parenteral, Therapy, Liposomes