The global increase in lung cancer cases, often marked by pulmonary nodules, underscores the critical importance of timely detection to mitigate cancer progression and reduce morbidity and mortality. The Faster R-CNN approach is a two-stage, high-precision nodule detection method designed for detecting small nodules, particularly in computed tomography (CT) images. This paper presents an improved Faster R-CNN by introducing an optimized multi-scale convolutional neural network (OMS-CNN) technique for feature map generation. This approach aims to achieve an optimal feature map through metaheuristic optimization by combining the last three layers of the VGG16 architecture. The advanced parameter-setting-free harmony search (PSF-HS) algorithm is utilized to implement this method, automatically adjusting the number of channels in the composite layers as a hyperparameter. The beetle antenna search (BAS) optimization algorithm is utilized to effectively initialize the kernel filter weights and biases in the composite layers, thereby enhancing training speed and detection accuracy. In the false-positive reduction stage, a combination of multiple 3D deep convolutional neural networks (3D DCNN) is designed to reduce false-positive nodules. The proposed model was evaluated using the LUNA16 and PN9 datasets. The results demonstrate that the OMS-CNN technique effectively extracted representative features of nodules at various sizes, achieving a sensitivity of 94.89% and a CPM score of 0.892. The comprehensive experiments illustrate that the proposed method can enhance detection sensitivity and manage the number of false positive nodules, thereby offering clinical utility and serving as a valuable point of reference.

The efficiency of state-of-the-art convolutional networks trained to detect lung cancer nodules depends on their feature extraction model. Various feature extraction models have been proposed based on convolutional networks, such as VGG-Net, or ResNet. It has been demonstrated that such models effectively extract features from objects in an image. However, their efficacy is limited when the objects of interest are very small, such as lung nodules. One of the widely used feature extraction models for detecting small objects is the VGG16 network. The model, which has a small kernel of$\mathbf{3}\times \mathbf{3}$and optimal layers, can extract the features of small objects with reasonable accuracy. In this article, feature maps are created by combining the last three layers of the VGG16 network to extract features of various sizes of nodules. This study utilizes a Region Proposal Network (RPN) to compare the accuracy of the feature map created in the proposed method and the original VGG16. An RPN is a fully-convolutional network that simultaneously predicts object bounds and objectness scores at each position. RPNs are trained end-to-end to generate high-quality region proposals, which Faster R-CNN uses for detection. In this article, we select 300, 1, 000 and 2, 000 regions chosen by the RPN network for each method; then, we calculate the recall for different Intersection over Union (IoU) ratios with ground-truth boxes. The results show that the feature map of the proposed method works more optimally than the feature map of different layers of VGG16 for extracting various sizes of nodules. Also, by reducing the number of selected region proposals, the recall of the proposed method has fewer changes than other methods.

This paper presents a CMOS optoelectronic lock-in amplifier (LIA) with semi-digital automatic phase alignment for optical sensing applications. The LIA incorporates a phase sensitive detection (PSD) channel and a phase alignment channel. A phase alignment loop generates the LIA reference clock, and automatically aligns the relative phase between the reference and the input signal through a phase interpolation providing unlimited (modulo 2π) phase shift. A finite state machine (FSM) is implemented in the digital domain to control the loop with low-power consumption and small chip area. The LIA is optimized to operate at a 50-kHz modulation frequency. The LIA is fully characterized optically and electrically, and measurement results are reported in this paper. The measured dynamic reserve and the sensitivity of the LIA are 35.37 dB and 296 mV/μW, respectively for a detection bandwidth of 50 Hz. The proposed LIA consumes an average power of 214 μW from a 1.8/3.3-V DC power supply.

Implantable wireless fiber biophotometry is one of the most effective technique to monitor specific cell types through Ca2+fluorescence sensing in live animals by avoiding fiber tethering and risks of breakage and injury which can occur in conventional apparatus. This demonstration will show the visitors a novel low-power, light-weight, and minimally invasive wireless optoelectronic interface enabling chronic brain fiber biophotometry in freely moving laboratory mice. The proposed device incorporates a custom integrated CMOS biosensor and off-the-shelf optical and electronic components such as a wireless transmitter, a LED as excitation light source, a microprocessor, and a miniaturized 3D-printed housing. The CMOS biosensor includes a two-step analog-to-digital converter (ADC) with a noise cancellation scheme enabling wide dynamic range and high-energy efficiency photocurrent quantization. A fiber biophotometry head-mountable 3D-printed housing holds in place the optical and electronic components and allows the utilization of a single mutlimode fiber to convey the excitation light and to collect the evoked fluorescence light.

This paper presents a high-sensitivity incremental discrete timeΣΔ analog-to-digital converter (ADC) with variable clock and on-chip decimation for biophotometry sensing. A digital correlated double sampling (CDS) scheme is merged with the decimation filter for providing energy- and area-efficient mean to suppress low-frequency noise. Chopper modulation and differential sensing using a dummy photodiode along with charge transfer switches are used as well to allow for the detection of ultra low-input low fluorescence light, down to a few femttowatt, by suppressing the low-frequency noise of theΣΔ modulator and the dark current of the photodetector. A variable clock scheme is used across the sensor operating phases (namely the reset conversion phase and the signal conversion phase) to decrease the biosensor conversion time. To decrease illumination time and save the excitation light source energy, the biosensor uses a short sensing duty cycle of 1.2 ms (12%) for a sampling period of 10 ms. The proposed optoelectronic biosensor is implemented in a 0.18-μm CMOS technology, consuming 56 μW from a 3.3/1.8-V supply voltage, while achieving a high signal-to-noise and distortion ratio of 101 dB and a minimum detectable current of <; 100-fArms, within conversion time of 1.2 ms. The proposed biosensor presents a FOM of 0.73 pJ/conv., which is among the best reported performances compared to previous solutions.

This paper presents a new biophotometry sensor embedding two individual building blocks, namely a low-noise sensing front-end and a 2ndorder continuous-time ΣΔ modulator (CTSDM), into a single module for enabling high-sensitivity and high energy-efficiency photo-sensing. In particular, a differential CMOS photodetector associated with a differential capacitive transimpedance amplifier (DCTIA)-based sensing front-end is merged with an incremental 2nd order 1-bit CTSDM to achieve a large dynamic range, low hardware complexity, and high energy-efficiency. The proposed optoelectronic biosensor is implemented in a 0.18-μm CMOS technology, consuming 8.23 μW from a 1.8-v supply voltage while achieving a peak SNDR of 62.5 dB, a dynamic range of 86 dB over a 50-Hz input bandwidth, a minimum detectable current of 90-fArms, and at a 25.6-KS/s sampling frequency. The proposed biosensor presents the best FOM of 0.0197 pJ/conv. among recently published biosensors.

This paper tackles the inverse problem of finding optimal configurations of magnetic gradient sources in Dipole Field Navigation (DFN), a magnetic navigation method proposed recently for the direct targeting of drugs. In DFN, a limited number of these gradient sources, called the cores, must be positioned properly around a patient in a Magnetic Resonance Imaging scanner to induce the required directional forces on the navigated therapeutic carriers. To overcome some limitations of the previous approach for solving this problem, here we propose a novel and conceptually simple multidimensional variant of the well-known Particle Swarm Optimization (PSO) algorithm. This variant, called Progressive Multidimensional PSO (PMD-PSO), enables a tradeoff between the quality and the complexity of the solutions by progressively increasing the number of dimensions in the search space. We apply this algorithm to the core placement problem using an improved fitness function for the evaluation of a core configuration given a vascular path towards a target. Experiments on simulated vasculatures show that, while the approach can effectively solve this inverse problem, PMD-PSO exhibits better performances for DFN compared with two other multidimensional PSO variants.

To achieve the effective navigation of microscale agents in the vascular network, a high magnetic field strength with high directional magnetic gradients are required. So far, the methods that have been investigated support only one of these specifications but not both. Here, we propose a new method dubbed dipole field navigation (DFN) that provides high field strength to bring magnetic agents at saturation magnetization with gradients exceeding 300 mT/m at any depth within the human body. For DFN, the high field strength is achieved by placing the patient in the tunnel of a clinical MRI scanner, while high gradients are generated by the distortions of the scanner's homogeneous field from larger ferromagnetic cores placed at specific locations outside the patient. The main challenge of DFN lies in the methods that are required to adequately place the cores in the tunnel. Here, a first method is presented to solve the inverse magnetic problem of positioning such a set of cores so that microscale agents could be guided through a desired path in the vascular network. As a first proof of concept, magnetic particles were steered successfully in three consecutive bifurcations in a 3-D in vitro network.

This paper reports the successful navigation of a 1-mm Chrome-Steel bead along three consecutive polymethyl methacrylate channels inside the bore of a 1.5-T magnetic resonance imaging (MRI) scanner. The bead traveled at a mean velocity of 14 cm·s-1. This was accomplished using an imaging gradient coil (IGC) insert located inside the MRI tube. While targeting one side of a bifurcation has been previously demonstrated using unidirectional gradient coils, this is the first time that magnetic resonance navigation (MRN) of a bead along consecutive channels is reported. Experimental results confirm that a clinical regular MRI can be used to propel a 1-mm device. In addition, when used at maximum power, IGC temperature rise becomes a serious issue that can ultimately damage the insert and limit the overall performance. Consequently, this paper aims to give some insight into coil temperature management for IGC-assisted procedures. A 33-min thermal stress test was carried out using 100% of the IGC power. Steady-state oscillation can be reached by interleaving propulsion periods with cooling periods, thus enabling longer propulsion procedures. Experimental data showed that the cooling time can be used for imaging purposes with no performance loss, thus enabling MRN-assisted procedures with multiplexed particle distribution assessment.

Research activities on nanorobotics comprise an emerging interdisciplinary technology area raising new scientific challenges and promising revolutionary advancement in applications such as medicine, biology, and industrial manufacturing. Nanorobots can be defined as intelligent systems with overall dimensions at or below the micrometer range that are made of assemblies of nanoscale components while exploiting the physics at such a scale, or as larger platforms capable of robotic operations at the nanoscale. In an effort to disseminate the current advances in this specialized field of robotics, and to stimulate discussion on the future research directions while invigorating research interests towards the development and applications of nanorobotic systems, a special issue of this issue of IEEE TRANSACTIONS ON ROBOTICS (T-RO) has been dedicated to recent developments in nanorobotics. This Special Issue presents a total of 15 papers in the most active areas of research in nanorobotics. Six papers are dedicated to actuation presenting recent advances in the implementation, control, and modelling of actuation methods suited for such robots operating in low Reynolds hydrodynamic conditions and, more specifically, helical propulsion with the force being induced from a rotating magnetic field, resonant magnetic actuation, and self-propelled microjets and platinum catalytic mobile nanorobots. Four papers cover the very active field of research in nanorobotics is in biological and medical applications. The remainder look at industrial applications of micro/nanorobotic manipulation systems.

Magnetic Resonance Navigation (MRN) relies on Magnetic Nanoparticles (MNPs) embedded in microcarriers or microrobots to allow the induction of a directional propelling force by 3-D magnetic gradients. These magnetic gradients are superposed on a sufficiently high homogeneous magnetic field (e.g. the Bo field of a MR scanner) to achieve maximum propelling force through magnetization saturation of the MNPs. As previously demonstrated by our group, such technique was successful at maintaining microcarriers along a planned trajectory in the blood vessels based on tracking information gathered using Magnetic Resonance Imaging (MRI) sequences from artifacts caused by the same MNPs. Besides propulsion and tracking, the same MNPs can be synthesized with characteristics that can allow for the diffusion of therapeutic cargo carried by these MR-navigable carriers through the Blood Brain Barrier (BBB) using localized hyperthermia without compromising the MRN capabilities. In the present study, localized hyperthermia induced by an alternating magnetic field (AC field) is investigated for the purpose of transient controlled disruption of the BBB and hence local delivery of therapeutic agents into the brain. Here, an external heating apparatus was used to impose a regional heat shock on the skull of a living mouse model. The effect of heat on the permeability of the BBB was assessed using histological observation and tissue staining by Evans blue dye. Results show direct correlation between hyperthermia and BBB leakage as well as its recovery from thermal damage. Therefore, in addition to on-command propulsion and remote tracking, the proposed navigable agents could be suitable for controlled opening of the BBB by hyperthermia and selective brain drug delivery.

This paper reports the successful navigation of Magnetotactic Bacteria (MTB) towards regions located inside a solid tumor using a computer controlled set of magnetic coils. MTB uses two flagella bundles connected to rotary molecular motors as a propulsion system enabling them to reach swimming velocities of 300µm·s−1without external source of power. Acting like autonomous microrobots, they can be remotely controlled by an appropriate magnetic guidance system as their swimming direction is predominantly determined by the direction of the ambient magnetic field. In order to cope with the harsh environment of the solid tumor and to bypass the lack of knowledge of the internal vessels architecture forming the route to the tumor, fundamental MTB motion properties are taken into account in addition to their ability to swim along the magnetic field. The studies revealed the presence of these bacteria in the necrotic zone of a solid tumor. Preliminary results suggest that not only the magnetic guidance can help enhancing the uniform distribution of MTB inside the tumor for therapeutic or diagnostic purposes, but the experimental data showed that they could perform accurately and efficiently under computer control, many of the tasks previously envisioned for future synthetic microrobots of only 1 to 2 micrometers in diameter and designed to operate in the human microvascular network.

A new actuation principle which permits omnidirectional steering for a swimming robot using a magnetic resonance imaging scanner is presented. The robot fish is made of a ferromagnetic head and a flexible tail. It is actuated by transverse oscillating magnetic gradients. The swimming performances of the robot fish are studied for varying tail length as well as varying actuation frequency and amplitude. Through a dimensional analysis, the important parameters influencing the swimming gait are identified and the mechanism of actuation is better understood. Considering the scaling of forces, this dimensional analysis leads us to believe that in the future the height and width of the fish robot could be miniaturised to sub-millimetre scale.

Magnetic Resonance Navigation (MRN) aims at navigating artificial or synthetic untethered micro-devices and microrobots using an upgraded clinical Magnetic Resonance Imaging (MRI) system. For larger MRI-based navigated entities, past experiments proved that software-based upgrades only were sufficient. But for microrobots with an overall diameter of only a few tens of micrometers for travelling in narrower blood vessels, hardware upgrades need to be added to the MR scanner, resulting in a MRN system capable of generating 3D magnetic propulsion gradients on the microrobots well above the ones that could be generated by a clinical MRI scanner relying on software-upgrades only. But with the variety of models of clinical scanners coped with many versions of related operating software dedicated to MR imaging, implementing such upgrades that could operate with these scanners becomes a real challenge. As such, a new MRN platform architecture independent of the types of MR scanners is proposed and preliminary experimental data validating the potential of such microrobotic navigation system architecture integrated with a commercially available scanner are reported. The expected steering capabilities of the platform were evaluated initially using a special probe in the form of a magnetic catheter mimicking an anisotropic microrobot. Such special probe also allowed for easier recordings of the gradient steering force that would be induced on such microrobot while validating the technique for catheter steering which is also an important aspect since catheterization is often used for releasing the microrobots in larger arteries. Similarly, MR tracking of the same microrobot was also validated with the new system, confirming that tracking feedback data can be gathered in order to perform closed-loop navigation control.

Many science fiction novels have envisioned swarms of artificial microrobots capable of performing complex collective tasks. Unfortunately, today's technological constraints have prevented such powerful concept to be a reality when considering artificial microrobots. In this paper, we show that a swarm of computer-controlled flagellated Magnetotactic Bacteria (MTB) acting as natural microrobots of approximately 1 to 2 micrometers in diameter can perform many of the same complex collective tasks envisioned with these futuristic self-propelled artificial microrobots. To prove the concept, magnetotaxis-based control has been used to coordinate a swarm made of thousands of these self-propelled natural microrobots to build in a collective effort, a miniature version of an ancient Egyptian pyramid.

A real-time positioning and tracking technique for untethered devices or robots magnetically propelled by a clinical magnetic resonance imaging (MRI) system is described. The local magnetic field induced by the device, composed of a ferromagnetic material, is used as a signature to localize the device on three one-dimensional projections. A high-precision 3D circular-motion system was used to assess the precision and accuracy of this method. The integration of this technique inside propulsion and imaging MRI sequences was also achieved to demonstrate the feasibility of this tracking scheme in a closed-loop control scheme. Finally, in vivo tracking during automatic navigation of an untethered device in the carotid artery of a living animal is demonstrated.

Experimental data and proofs of concepts are used to show the feasibility of providing the basic components and functionalities required for the implementation of intelligent untethered 150 × 300µm bacterial microrobots capable of sophisticated collective tasks under computer supervision and coordination. More specifically, we show that it is possible to embed within such microrobots, photovoltaic cells supplying ∼4µW necessary to power an internal microelectronic circuit providing embedded intelligence with the capability to communicate commands and data wirelessly to an external computer. We also show that such data or commands transmitted wirelessly could be used to instruct an external computer to send a swarm of flagellated bacteria to move such microrobots towards a specific target based on various sensory information acquired with specific sensors embedded in each microrobots. Similar to chemotaxis used by several species of flagellated bacteria, the algorithms used to move such microrobots could be governed by a larger range of sensory means, leading to what we refer to here as sensotaxis-based hybrid microrobots. The possibility of transmitting a request to a central computer to send a swarm of flagellated magnetotactic bacteria to provide propulsion and steering in order to move accurately to desired locations would allow such microrobots to perform collective tasks. A simple example suggesting the possibility of implementing accurate collective tasks by such hybrid microrobots is demonstrated experimentally where a microstructure emulating a V-shaped microrobot is moved and rotated autonomously using a swarm of approximately 3000 flagellated bacteria towards another similar V-shaped microstructure to form the character ‘M’ as in Microrobot.

Bacteria can be used as computer-controlled bioactuators and means of propulsion for microrobots and other micro-scaled entities to accomplish precise operations as first proposed by our research group in [1] and demonstrated later experimentally in [2]. The last reference confirmed that the propulsion force provided by the flagella being connected to molecular motors embedded in the bacterial cell, could be exploited to replace more conventional technologies being presently used in robotics but which could not be implemented at such a scale. In a coherent effort, our group also pioneered a method of not only harnessing instead of mimicking nature by using flagellated bacteria and more specifically Magnetotactic Bacteria (MTB) for propulsion and transport, but also for the controlled steering or computerized directional swimming control of bacterial micronanorobots [3].

Our group has previously demonstrated that magnetic nanoparticles (MNP) embedded in microrobots can be used for propulsion and tracking in the human vascular network while being guided by an MRI platform. Here, we show that the same magnetic nanoparticles can also be exploited to perform various functions including but not limited to hyperthermic drug release actuators. Specifically, we synthesized vascular microrobots by embedding MNP in N-isopropylacrylamide (NIPA) thermo responsive hydrogel. We experimentally demonstrate the decrease in volume of the hydrogel microrobot in response to AC magnetic heating, a property that allows microrobots to adapt to blood vessels of various diameters. This type of hydrogel is not only able to reduce size in response to temperature elevations but it can also be used to release possible therapeutic agents previously trapped within the hydrogel. Here, NIPA hydrogel samples were placed inside an AC magnetic field of 116 Oe at 145 kHz. Temperature elevations as well as change in hydrogel volume were recorded.

A novel magnetic resonance (MR)-tracking method specifically developed to locate the ferromagnetic core of an untethered microdevice, microrobot, or nanorobot for navigation or closed-loop control purpose is described. The tracking method relies on the application of radio-frequency (RF) excitation signals tuned to the equipotential magnetic curves generated by the magnetic signature of the object being tracked. Positive contrast projections are obtained with reference to the position of the magnetic source. A correlation function performed on only one k-space line for each of the three axes and corresponding to three projections, is necessary to obtain a 3-D location of the device. In this study, the effects of the sphere size and the RF frequency offset were investigated in order to find the best contrast noise ratio (CNR) for tracking. Resolution and precision were also investigated by proper measurement of the position of a ferromagnetic sphere by magnetic resonance imaging (MRI) acquisition and by comparing them with the real position. This method is also tested for a moving marker where the positions found by MRI projections were compared with the ones taken with a camera. In vitro and in vivo experiments show the operation of the technique in tortuous phantom and in animal models. Although the method was developed in the prospect of new interventional MR-guided endovascular operations based on miniature untethered devices, it could also be used as a passive tracking method using tools such as catheters or guide wires.

Models for MRI-based magnetic propulsion of untethered medical microrobots were validated both in vitro and in vivo using magnetic beads. In accordance with the theoretical models, a clinical MRI system has the capability to propel magnetic spheres with maximum velocity in blood vessels approximately twice the diameter of the device being navigated. The preliminary models were in accordance with data obtained in experiments performed in the carotid artery of a living swine where a 1.5 mm sphere was propelled with a velocity of 13 cm/s. These models were used in this paper to extrapolate the magnetic field gradients that will be required for propulsion and steering of magnetic particles and applicable for microrobots in blood vessels of various sizes, from the aorta to the capillaries.

A new cooling system for a fleet of scientific instruments in the form of miniature wireless robots designed for interactions at the nanometer-scale is assessed to determine its limitations. Unlike other approaches, the use of a cooling chamber allows us to remove an embedded cooling system and maintain the overall size of each robot to a minimum, hence increasing the density of instruments per surface area and resulting in enhanced performance of the platform. The goal of this paper is to assess the capacity of this cooling system; not only to remove heat but also to reduce temperature fluctuations and difference in temperature levels among the robots to maintain each robot within an operational temperature range of 0–70$^{\circ}{\rm C}$. One hundred dummy robots were therefore placed in a custom-built cooling chamber which uses forced air convection. The temperature levels of the dummy robots were recorded with power dissipations from 0 to 15 W/robot and a maximum air flow rate of 0.5 m/s. It was determined that the maximum range in difference in temperature levels among the dummy robots increases by$\sim{\hbox {20}}\;^{\circ}$C per additional 5 W/robot of power dissipation with an initial difference of$\sim{\hbox {40}}\;^{\circ}$C at 5 W/robot. An estimated total power dissipation of 10 W/robot was determined to be a safe limit in order to maintain the operating temperature range of the robots between 0–70$^{\circ}$C. For power dissipation over 10 W/robot, additional compensation methods are required.

The preliminary design of photovoltaic cells to be embedded in untethered aqueous microrobots, a few hundred micrometers in overall length, is briefly described. A total of 4 cells with an estimated efficiency of 12.5% should provide up to 100 microamperes of photonic current to the electronics embedded in each untethered microrobot from an incident source of green light. The need for power has been minimized through the use of magnetotactic bacteria (MTB) acting as embedded micro-actuators to propel the microrobots in an aqueous medium. Controlling the direction of propulsion with the onboard electronics would be performed by exploiting magnetotaxis inherent in MTB. Here, a small electrical current provided by the photovoltaic cells and flowing in a controlled manner in a special embedded conductor network would be sufficient to exert a torque on a chain of magnetosomes in each bacterium. Such approach allows us to independently change their direction of motion when pushing each microrobot

The concept of a nanorobotic platform based on a fleet of miniature instrumented robots capable of atomic-scale operations has been proposed. Although such an approach offers significant advantages compared to more traditional approaches, many technical challenges remain to be resolved. As such, being able to position the instrument embedded onto each robot with atomic-scale precision is a critical, yet challenging problem. All known positioning techniques, including, but not limited to, interferometry, cannot be applied in this case. This paper suggests a novel approach where coarse positioning through optical means is coupled to surface analysis to achieve atomic scale precision. A special line-based pattern engraved on a surface is used to guide and accelerate the robot's instrument positioning by delimiting a matrix of work windows where atomic positioning through atom counting takes places. The NanoWalker research project serves as an implementation contest for this grid. Its current version is etched on Highly Oriented Pyrolytic Graphite (HOPG) and imaged with commercial Scanning Probe Microscopes (SPM).

The development of a new nanorobotics platform based on a fleet of scientific instruments configured as wireless miniature robots capable of fast operations at the nanoscale in a cooling chamber has been proposed. To cope with the excessive heat of the robots, the heat dissipation is enhanced by filling the chamber with cooled Helium. While the high-powered robots can be maintained at relatively low operating temperatures, the infrared positioning and communication systems needed to coordinate the robots, would without protection, be permanently damaged when exposed to such low ambient temperature levels. This paper describes the design of an infrared and communication unit capable to operate under these excessive conditions while fulfilling the communication and coordination requirements of such a nanorobotics platform.

The emerging fields of nanosciences and nanoengineering will provide the ability to work at the molecular level to create larger structures with new molecular organization. This understanding and control over the fundamental building blocks of all physical entities will lead to new emerging opportunities in factory automation. Although research in this field is very active, little has been done toward increasing the throughput rate, a factor that will be critically important in future nanofactories. An approach for the implementation of scaleable and high-throughput nanofactories based on a fleet of miniature autonomous robots capable of operations at the atomic-scale is described.

We propose to bring the instruments to the samples in the form of miniature wireless instrumented robots called the NanoWalkers. With the NanoWalker robot approach, instrumentations and throughput requirements can be adjusted extremely fast by simply adding, replacing, or removing robots at will. It is the aim of this project to develop a powerful and flexible environment that we believe may revolutionize the way drug, biological, material discovery, and characterization will be performed in the future.