Robotic Workstation Research Articles

In Vitro Resistance-Predicting Studies and In Vitro Resistance-Related Parameters-A Hit-to-Lead Perspective.

Despite the urgent need for new antibiotics, very few innovative antibiotics have recently entered clinics or clinical trials. To provide a constant supply of new drug candidates optimized in terms of their potential to select for resistance in natural settings, in vitro resistance-predicting studies need to be improved and scaled up. In this review, the following in vitro parameters are presented: frequency of spontaneous mutant selection (FSMS), mutant prevention concentration (MPC), dominant mutant prevention concentration (MPC-D), inferior-mutant prevention concentration (MPC-F), and minimal selective concentration (MSC). The utility of various adaptive laboratory evolution (ALE) approaches (serial transfer, continuous culture, and evolution in spatiotemporal microenvironments) for comparing hits in terms of the level and time required for multistep resistance to emerge is discussed. We also consider how the hit-to-lead stage can benefit from high-throughput ALE setups based on robotic workstations, do-it-yourself (DIY) continuous cultivation systems, microbial evolution and growth arena (MEGA) plates, soft agar gradient evolution (SAGE) plates, microfluidic chips, or microdroplet technology. Finally, approaches for evaluating the fitness of in vitro-generated resistant mutants are presented. This review aims to draw attention to newly emerged ideas on how to improve the in vitro forecasting of the potential of compounds to select for resistance in natural settings.

Virtual Simulation and Experiment of Quality Inspection Robot Workstation

(1) Background: Quality inspection robots are widely used in automated production lines. However, the design cycle is long, iteration costs are high, and algorithm development is challenging. It is difficult to perform effective validation during the design phase. Applying virtual reality technology to simulate quality inspection robot workstations offers a new approach to addressing the issues. (2) Methods: The research creates a simulation platform for quality inspection robot workstations based on a virtual reality architecture. The platform creates an immersive quality inspection robot workstation operation interface and conducts testing of the inspection process, thereby validating the rationality of the quality inspection robot workstation design. Building upon this foundation, we conducted experimental comparisons of various defect detection algorithms. (3) Results: Compared to the traditional YOLOv7 algorithm, the improved YOLOv7 algorithm achieved an 18.1% increase in recognition precision. Experimental results demonstrate that the quality inspection robot workstation simulation platform can be applied to validating workstation design proposals. (4) Conclusions: It has a positive impact on reducing the research and development costs of quality inspection robot workstations and shortening the defect recognition algorithm development cycle.

Control Robotic Arm Workstation Using IoT System for Education

Robotics play an important role in the era of modern technology. Robots can be defined as mechanical devices programmed to perform manipulative tasks under automatic control. Robotic arm is usually used in conjunction with aids such as machines and fixtures. As advancement in robot technology have become an integral part of automation in the manufacturing process. This research gives an idea of how robotic arm can be controlled using internet systems. Therefore, it also a way to reduce the risk of humans being in dangerous areas. The emergence of technology has managed to witness the evolvement of a new era known as the Internet of Things (IoT). The purpose of the research is to control robotic arm workstation using IoT system for education. The research is use Arduino uno Wi-Fi microcontroller and blink application to control IoT system. By using Arduino microcontroller, the robotic arm can directly connect to the internet. Therefore, the implementation of control robotic arm using IoT based on internet connectivity of students.

Simulation and experimental study of die-casting pickup robot

To improve the efficiency of die-casting machine pickup, the combination of SolidWorks and RobotStudio is proposed to establish a simulation workstation. In this paper, the key mechanism analysis and design of the die-casting machine pickup robot are used to determine the robot body and end-effector. SolidWorks three-dimensional software is used for die-casting pickup robot’s overall mechanical structure and workstation peripheral equipment modeling. The RobotStudio software is used for the corresponding model planning layout and Smart components to write to achieve die-casting robot workstation efficient pickup work program writing and simulation debugging. Experimental results show that the die-casting machine pickup robot completed the pickup behavior. The system has the advantages of fast response speed, high positioning accuracy, and reliable operation, effectively improving the efficiency of the production line.

A Digital Twin Design Based on Robot Workstation

A Digital Twin Design Based on Robot Workstation

Optimisation of Product Recovery Options in End-of-Life Product Disassembly by Robots

In a circular economy, strategies for product recovery, such as reuse, recycling, and remanufacturing, play an important role at the end of a product’s life. A sustainability model was developed to solve the problem of sequence-dependent robotic disassembly line balancing. This research aimed to assess the viability of the model, which was optimised using the Multi-Objective Bees Algorithm in a robotic disassembly setting. Two industrial gear pumps were used as case studies. Four objectives (maximising profit, energy savings, emissions reductions and minimising line imbalance) were set. Several product recovery scenarios were developed to find the best recovery plans for each component. An efficient metaheuristic, the Bees Algorithm, was used to find the best solution. The robotic disassembly plans were generated and assigned to robotic workstations simultaneously. Using the proposed sustainability model on end-of-life industrial gear pumps shows the applicability of the model to real-world problems. The Multi-Objective Bees Algorithm was able to find the best scenario for product recovery by assigning each component to recycling, reuse, remanufacturing, or disposal. The performance of the algorithm is consistent, producing a similar performance for all sustainable strategies. This study addresses issues that arise with product recovery options for end-of-life products and provides optimal solutions through case studies.

Robot dispatching problem for compact storage and retrieval systems with dual-command transactions

A robotic compact storage and retrieval system (RCSRS) is a grid-based system that has been popularly implemented by online retailers around the world recently. This article addresses a robot dispatching problem for RCSRS, aiming to reduce robot empty travelling time and workstation idle time. The robot dispatching problem is to assign tasks to robots when the task sequences in workstations are given. Additionally, the robots follow a fast dual-command transaction process in this problem. Hence, a mixed integer programming model catering for the dual-command transaction process is formulated to optimize system performance. Furthermore, an adaptive neighbourhood search with an ε-greedy algorithm is proposed to solve the problem. The experimental results substantiate the superiority of the authors' proposed algorithm compared to various algorithms used in practice and discussed in the relevant literature. Moreover, optimal system configurations for the instances generated are suggested.

Extensive Expression of the Virulome Related to Antibiotic Genotyping in Nosocomial Strains of Klebsiella pneumoniae.

The emergence of hyper-virulent and multidrug-resistant (MDR) strains of Klebsiella pneumoniae isolated from patients with hospital- and community-acquired infections is a serious health problem that increases mortality. The molecular analysis of virulome expression related to antimicrobial-resistant genotype and infection type in K. pneumoniae strains isolated from patients with hospital- and community-acquired infections has been poorly studied. In this study, we analyzed the overall expression of the virulence genotype associated with the antimicrobial resistance genotype and pulse field gel electrophoresis (PFGE) type (PFtype) in K. pneumoniae. We studied 25 strains of K. pneumoniae isolated from patients who developed bacteremia and pneumonia during their hospital stay and 125 strains from outpatients who acquired community-acquired infections. Susceptibility to 12 antimicrobials was determined by Kirby-Bauer. The identification of K. pneumoniae and antibiotic-resistance genes was performed using polymerase chain reaction (PCR). To promote the expression of the virulence genes of K. pneumoniae, an in vitro infection model was used in human epithelial cell lines A549 and A431. Bacterial RNA was extracted with the QIAcube robotic workstation, and reverse transcription to cDNA was performed with the Reverse Transcription QuantiTect kit (Qiagen). The determination of the expression of the virulence genes was performed by real-time PCR. In addition, 57.3% (n = 86) of the strains isolated from patients with hospital- and community-acquired infections were multidrug-resistant (MDR), mainly to beta-lactam antibiotics (CB, AM, CFX, and CF), aminoglycosides (GE), quinolones (CPF and NOF), nitrofurantoin (NF), and sulfamethoxazole/trimethoprim (SXT). The most frequently expressed genes among strains isolated from hospital- and community-acquired infections were adhesion-type, ycfm (80%), mrkD (51.3%), and fimH (30.7%); iron uptake, irp2 (84%), fyuA (68.7%), entB (64.7%), and irp1 (56.7%); and protectins, rpmA (26%), which were related to antibiotic-resistance genes, blaTEM (96%), blaSHV (64%), blaCITM (52.6%), blaCTXM-1 (44.7%), tetA (74%), sul1 (57.3%), aac(3)-IV (40.7%), and aadA1 (36%). The results showed the existence of different patterns of expression of virulome related to the genotype of resistance to antimicrobials and to the PFtypes in the strains of K. pneumoniae that cause hospital- and community-acquired infections. These findings are important and may contribute to improving medical treatment strategies against infections caused by K. pneumoniae.

Mathematical and computational models in spheroid-based biofabrication.

Ubiquitous in embryonic development, tissue fusion is of interest to tissue engineers who use tissue spheroids or organoids as building blocks of three-dimensional (3D) multicellular constructs. This review presents mathematical models and computer simulations of the fusion of tissue spheroids. The motivation of this study stems from the need to predict the post-printing evolution of 3D bioprinted constructs. First, we provide a brief overview of differential adhesion, the main morphogenetic mechanism involved in post-printing structure formation. It will be shown that clusters of cohesive cells behave as an incompressible viscous fluid on the time scale of hours. The discussion turns then to mathematical models based on the continuum hydrodynamics of highly viscous liquids and on statistical mechanics. Next, we analyze the validity and practical use of computational models of multicellular self-assembly in live constructs created by tissue spheroid bioprinting. Finally, we discuss the perspectives of the field as machine learning starts to reshape experimental design, and modular robotic workstations tend to alleviate the burden of repetitive tasks in biofabrication. STATEMENT OF SIGNIFICANCE: Bioprinted constructs are living systems, which evolve via morphogenetic mechanisms known from developmental biology. This review presents mathematical and computational tools devised for modeling post-printing structure formation. They help achieving a desirable outcome without expensive optimization experiments. While previous reviews mainly focused on assumptions, technical details, strengths, and limitations of computational models of multicellular self-assembly, this article discusses their validity and practical use in biofabrication. It also presents an overview of mathematical models that proved to be useful in the evaluation of experimental data on tissue spheroid fusion, and in the calibration of computational models. Finally, the perspectives of the field are discussed in the advent of robotic biofabrication platforms and bioprinting process optimization by machine learning.

The clinical application of neuro-robot in the resection of epileptic foci: a novel method assisting epilepsy surgery.

During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epileptic foci. Here, we present a neuro-robotic navigation system that is specifically designed for resection of MRI negative epileptic foci. We recruited 52 epileptic patients, and randomly assigned them to treatment group with either neuro-robotic navigation or conventional neuronavigation system. For each patient, in the neuro-robotic navigation group, we integrated multimodality imaging including MRI and PET-CT into the robotic workstation and marked the boundary of foci from the fused image. During surgery, this boundary was delineated by the robotic laser device with high accuracy, guiding resection for the surgeon. For deeply seated foci, we exploited the neuro-robotic navigation system to localize the deepest point with biopsy needle insertion and methylene dye application to locate the boundary of the foci. Our results show that, compared with the conventional neuronavigation, the neuro-robotic navigation system performs equally well in MRI positive epilepsy patients (ENGEL I ratio: 71.4% vs 100%, p = 0.255) systems and show better performance in patients with MRI-negative focal cortical dysplasia (ENGEL I ratio: 88.2% vs 50%, p = 0.0439). At present, there are no documented neurosurgery robots with similar function and application in the field of epilepsy. Our research highlights the added value of using neuro-robotic navigation systems in resection surgery for epilepsy, particularly in cases that involve MRI-negative or deep-seated epileptic foci.

Novel Robotic Arm Working-Area AI Protection System

From traditionally handmade items to the ability of people to use machines to process and even to human-robot collaboration, there are many risks. Traditional manual lathes and milling machines, sophisticated robotic arms, and computer numerical control (CNC) operations are quite dangerous. To ensure the safety of workers in automated factories, a novel and efficient warning-range algorithm is proposed to determine whether a person is in the warning range, introducing YOLOv4 tiny-object detection algorithms to improve the accuracy of determining objects. The results are displayed on a stack light and sent through an M-JPEG streaming server so that the detected image can be displayed through the browser. According to the experimental results of this system installed on a robotic arm workstation, it is proved that it can ensure recognition reaches 97%. When a person enters the dangerous range of the working robotic arm, the arm can be stopped within about 50 ms, which will effectively improve the safety of its use.

An automated micro solid phase extraction gas chromatography–mass spectrometry (μSPE-GC–MS) detection method for geosmin and 2-methylisoborneol in drinking water

Geosmin and 2-methylisoborneol (2-MIB) are amongst the most common earthy and musty taste and odour (T&O) compounds found in drinking water. With low odour threshold detection limits below 10 ng L−1, and the complexity of raw water matrices, these two compounds provide a significant challenge for water companies globally. In this research, for the first time, a novel and fully automated micro-solid phase-extraction (μSPE) method coupled with gas chromatography (GC)–mass spectrometry (MS) has been developed for the detection of geosmin and 2-MIB for drinking water analysis. The new automated method described herein is environmentally friendly requiring low raw water sample volumes, of 25 mL, and only 50 μL of elution solvent. Our μSPE-GC–MS method exhibits excellent linearity for both compounds (R2 > 0.999) and low limits of detection of 2.0 ng L−1 and 4.3 ng L−1 for geosmin and 2-MIB, respectively. The method showed excellent recovery rates (95.1–100.1%) and good precision (RSD < 7%) in raw sample matrices. Our approach is fully automated onto a robotic workstation which can be readily integrated into a laboratory workflow for routine water analysis. Furthermore, the method has excellent potential to be incorporated within a portable system for onsite analysis.

Understanding adsorption behavior of antiviral labyrinthopeptin peptides in anion exchange chromatography

Lantipeptides from bacterial sources are increasingly important as biopharmaceuticals because of their broad range of applications. However, the availability of most lantipeptides is low, and systematic approaches for downstream processing of this group of peptides is still lacking. Model-based development for chromatographic separations has proven to be a useful tool for developing reliable purification processes. One important compound of such a model is the adsorption behavior of the components of interest. In ion-exchange chromatography, the adsorption equilibrium between salt and proteins can be described using the steric mass action (SMA) formalism. Beyond, the model parameters may be related to the lanthipeptides physico-chemical properties.In this study, the antiviral lantipeptides labyrinthopeptin A1 and A2, purified from Actinomadura namibiensis culture broth, were characterized for their adsorption behavior in anion-exchange chromatography in the range from pH 5.0–7.4. The experiments necessary to determine the three SMA parameters were chosen in a way to limit the amount of peptides needed. Linear gradient elution was applied successfully to separate A1 and A2 and to determine the characteristic charge νi and the equilibrium constant keqi. Batch adsorption experiments using a robotic workstation for high throughput and accuracy provided non-linear adsorption isotherms and the steric factor σi.Labyrinthopeptin A1 and A2 show a very different adsorption behavior even though the fundamental structure of the two peptides is similar. keq of A1 ranging from 0.18 to 0.88 are approximately one order of magnitude smaller than that of A2 ranging from 3.44 to 9.73 indicating the higher affinity of A2 to the stationary phase. At pH 7.0 σ was 1.12 and 0.60 for A1 and A2, respectively which was expected based on the molecular weight of the peptides. The characteristic charge for both peptides was also theoretically estimated from the amino acids involved in electrostatic interactions which was in good agreement with experimental data. Thereby, this work provides an useful approach to estimate SMA parameters based on simple structural information that can be applied early in chromatographic ion-exchange process development for peptides and may help adapting the processes for future designed lanthipeptides.

Process Simulation and Optimization of Arc Welding Robot Workstation Based on Digital Twin

For the welding cell in the manufacturing process of large excavation motor arm workpieces, a system framework, based on a digital twin welding robot cell, is proposed and constructed in order to optimize the robotic collaboration process of the welding workstation with digital twin technology. For the automated welding cell, combined with the actual robotic welding process, the physical entity was digitally modeled in 3D, and the twin welding robot operating posture process beats and other data were updated in real time, through real-time interactive data drive, to achieve real-time synchronization and faithful mapping of the virtual twin as well as 3D visualization and monitoring of the system. For the robot welding process in the arc welding operation process, a mathematical model of the kinematics of the welding robot was established, and an optimization method for the placement planning of the initial welding position of the robot base was proposed, with the goal of smooth operation of the robot arm joints, which assist in the process simulation verification of the welding process through the virtual twin scenario. The implementation and validation process of welding process optimization, based on this digital twin framework, is introduced with a moving arm robot welding example.

Research on preprocessing of winding trajectory of composite type IV pressure vessel based on robot

Herein, a smooth preprocessing method of robotic end-effector trajectory, based on Nurbs curve is proposed for obtaining the complete and stable envelope trajectory of the robot. Initially, the winding pattern of pressure vessel based on non-geodesic is deduced, followed by positioning of yarn point based on doffing point distribution and preprocessing of the trajectory through Nurbs curve. Variation trend and stationarity of velocity and acceleration in carriage and cross-carriage directions in Cartesian coordinate system are analyzed. Finally, the winding experiment of type IV pressure vessel is wound with the robotic winding workstation. Results show that the fiber winding can be carried out stably by the end of the robot. The realtime movement curve of the robot is consistent with the simulation curve, and the pressure liner is completely covered without yarn sliding and overhead problems, verifying the feasibility of the as-reported preprocessing method.

Automated photo-aligned liquid crystal elastomer film fabrication with a low-tech, home-built robotic workstation

Laboratory procedures are often considered so unique that automating them is not economically justified – time and resources invested in designing, building and calibrating the machines are unlikely to pay off. This is particularly true if cheap labour force (technicians or students) is available. Yet, with increasing availability and dropping prices of many off-the-shelf components such as motorised stages, grippers, light sources (LEDs and lasers), detectors (high resolution, fast cameras), as well as user-friendly programmable microprocessors, many of the repeatable tasks may soon be within reach of either custom-built or universal lab robots. Building on our previous work on fabrication, characterization and applications of light-responsive liquid crystal elastomers (LCEs) in micro-robotics and micro-mechanics, in this paper we present a robotic workstation that can make LCE films with arbitrary molecular orientation. Based on a commercial 3D printer, the RoboLEC (Robot for LCE fabrication) performs precision component handling, structured light illumination, liquid dispensing and UV-triggered polymerization, within a four-hour-long procedure. Thus fabricated films with patterned molecular orientation are compared to the same, but handmade, structures.

Using Physics-Based Digital Twins and Extended Reality for the Safety and Ergonomics Evaluation of Cobotic Workstations

Cobotic workstations in industrial plants involve a new kind of collaborative robots that can interact with operators. These cobots enable more flexibility and they can reduce the cycle time and the floor space of the workstation. However, cobots also introduce new safety concerns with regard to operators, and they may have an impact on the workstation ergonomics. For those reasons, introducing cobots in a workstation always require additional studies on safety and ergonomics before being applied and certified. Certification rules are often complex to understand. We present the SEEROB framework for the Safety and Ergonomics Evaluation of ROBotic workstations. The SEEROB framework simulates a physics-based digital twin of the cobotic workstation and computes a large panel of criteria used for safety and ergonomics. These criteria may be processed for the certification of the workstation. The SEEROB framework also uses extended reality technologies to display the digital twin and its associated data: users can use virtual reality headsets for the design of non-existing workstations, and mixed reality devices to better understand safety and ergonomics constraints on existing workstations. The SEEROB framework was tested on various laboratory and industrial use cases, involving different kinds of robots.

A 3D printable adapter for solid-state fluorescence measurements: the case of an immobilized enzymatic bioreceptor for organophosphate pesticides detection

The widespread use of pesticides in the last decades and their accumulation into the environment gave rise to major environmental and human health concerns. To address this topic, the scientific community pointed out the need to develop methodologies to detect and measure the presence of pesticides in different matrices. Biosensors have been recently explored as fast, easy, and sensitive methods for direct organophosphate pesticides monitoring. Thus, the present work aimed at designing and testing a 3D printed adapter useful on different equipment, and a membrane support to immobilize the esterase-2 from Alicyclobacillus acidocaldarius (EST2) bioreceptor. The latter is labelled with the IAEDANS, a bright fluorescent probe. EST2 was selected since it shows a high specificity toward paraoxon. Our results showed good stability and replicability, with an increasing linear fluorescent intensity recorded from 15 to 150 pmol of labelled EST2. Linearity of data was also observed when using the immobilized labelled EST2 to detect increasing amounts of paraoxon, with a limit of detection (LOD) of 0.09 pmol. This LOD value reveals the high sensitivity of our membrane support when mounted on the 3D adapter, comparable to modern methods using robotic workstations. Notably, the use of an independent support significantly simplified the manipulation of the membrane during experimental procedures and enabled it to match the specificities of different systems. In sum, this work emphasizes the advantages of using 3D printed accessories adapted to respond to the newest research needs.Graphical abstract

Ergonomics and Human Factors as a Requirement to Implement Safer Collaborative Robotic Workstations: A Literature Review

There is a worldwide interest in implementing collaborative robots (Cobots) to reduce work-related Musculoskeletal Disorders (WMSD) risk. While prior work in this field has recognized the importance of considering Ergonomics &amp; Human Factors (E&amp;HF) in the design phase, most works tend to highlight workstations’ improvements due to Human-Robot Collaboration (HRC). Based on a literature review, the current study summarises studies where E&amp;HF was considered a requirement rather than an output. In this article, the authors are interested in understanding the existing studies focused on Cobots’ implementation with ergonomic requirements, and the methods applied to design safer collaborative workstations. This review was performed in four prominent publications databases: Scopus, Web of Science, Pubmed, and Google Scholar, searching for the keywords ‘Collaborative robots’ or ‘Cobots’ or ‘HRC’ and ‘Ergonomics’ or ‘Human factors’. Based on the inclusion criterion, 20 articles were reviewed, and the main conclusions of each are provided. Additionally, the focus was given to the segmentation between studies considering E&amp;HF during the design phase of HRC systems and studies applying E&amp;HF in real-time on HRC systems. The results demonstrate the novelty of this topic, especially of the real-time applications of ergonomics as a requirement. Globally, the results of the reviewed studies showed the potential of E&amp;HF requirements integrated into HRC systems as a relevant input for reducing WMSD risk.

Object-Process Methodology as an Alternative to Human Factors Task Analysis.

We define and demonstrate the use of OPM-TA-a model-based task analysis (TA) framework that uses object-process methodology (OPM) ISO 19450 as a viable alternative to traditional TA techniques. A variety of different TA methods exist in human factors engineering, and several of them are often applied successively for a broad task representation, making it difficult to follow. Using OPM-TA, we modeled how an International Space Station (ISS) astronaut would support extravehicular activities using the existing robotic arm workstation with a new control panel and an electronic procedure system. The modeling employed traditional TA methods and the new OPM-TA approach, enabling a comparison between them. While the initial stages of modeling with OPM-TA follow those of traditional TA, OPM-TA modeling yields an executable and logically verifiable model of the entire human-robot system. Both OPM's hierarchical set of diagrams and the equivalent, automatically generated statements in a subset of natural language text specify how objects and processes relate to each other at increasingly detailed levels. The graphic and textual OPM modalities specify the system's architecture, which enables its function and benefits its users. To verify the model logical correctness model, we executed it using OPM's simulation capability. OPM-TA was able to unify traditional TA methods and expand their capabilities. The formal yet intuitive OPM-TA approach fuses and extends traditional TA methods, which are not amenable to simulation. It therefore can potentially become a widely used means for TA and human-machine procedure development and testing.