Robotic Tools Research Articles

Comparison of Implant Placement Accuracy Between Manual, Robot-Assisted, Computer-Navigated, Augmented Reality Navigated, Patient-Specific Instrumentation, and Accelerometer Navigated Total Hip Arthroplasty: A Systematic Review and Network Meta-Analysis.

Malpositioning of the acetabular cup during total hip arthroplasty (THA) can lead to complications. Robotic surgery and navigation techniques aim to address this issue, but there is limited evidence regarding which method can achieve better clinical outcomes. Therefore, this network meta-analysis (NMA) aimed to compare the efficacy of various navigation methods. This NMA of prospective randomized controlled trials compared robot-assisted systems (RAS), computer-assisted navigation systems (CAS), augmented reality-based portable navigation (AR), patient-specific instrumentation (PSI), portable accelerometer-based navigation (PN), and conventional methods (C) for THA procedures. We searched MEDLINE, EMBASE, Cochrane, Central Register of Controlled Trials, International Clinical Trials Platform Search Portal, and ClinicalTrials.gov. databases. The primary outcomes included revision surgery and postoperative clinical scores, and the secondary outcomes encompassed cup placement accuracy, acetabular cup placement outliers from the Lewinnek safe zone, surgical time, and complications. We used a Bayesian random-effects NMA, and confidence of evidence was assessed using confidence in NMA. We identified 45 studies including 2,122 patients. We did not find large differences in revision surgery, clinical outcome scores, cup inclination, or anteversion angle accuracy among the modalities. AR, CAS, and PSI exhibited a lower risk of outliers from safe zones than C. In addition, RAS and CAS had a longer surgical time than C. Robotic and navigation tools did not reduce the revision risk or enhance clinical outcomes. AR, CAS, PSI, and PN may decrease the risk of cup placement outliers in safe zones. However, the cup placement accuracy was equivalent, and the surgical time may be longer in RAS and CAS than in C. Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.

Suitability of UR5 Robot for Robotic 3D Printing

The present paper describes the measurement of the drift of unidirectional pose accuracy, repeatability, and static compliance of a collaborative robot employing a measurement methodology that relies on the description of a virtual ISO cube placed in the robot’s workspace. The measurements aimed to investigate and assess the suitability of the UR5 six-axis collaborative robot for its application in robotic 3D printing. An experimental laboratory measurement workstation was constructed to perform the measurements, and control measurements were performed. The measurements involved describing the TCP point of the robot tool at five measurement points located in a virtual ISO cube during a minimum of 30 repeated measurement cycles. A camera and six linear incremental sensors with assessment units were used for the measurements. The measurements were performed in compliance with the regulations of STN ISO 9283 standard for this type of measurement. As a result of the measurements, the technical specifications of the drift and static compliance of the controlled robotic arm were verified, and the results were compared with the values specified by the manufacturer. Following the measurements and assessment of the results, it was possible to assess the suitability of the used UR5 robotic arm for its application in robotic 3D printing and to propose possible recommendations for the calibration of the robot and the process settings of the printing system for the production of objects using FDM technology.

Unleashing the potential of AI in modern healthcare: Machine learning algorithms and intelligent medical robots

Artificial intelligence (AI) is playing an increasingly vital role in transforming the medical field, particularly in areas like medical imaging, clinical decision-making, pathology, and minimally invasive surgery. The rapid growth of medical data and the continuous refinement of machine learning algorithms have propelled AI's integration into healthcare. This study explores the advancements and applications of AI, specifically machine learning algorithms and intelligent medical robots, in enhancing diagnostics, treatment, and healthcare delivery. A comprehensive review of current AI applications in healthcare, including its use in medical imaging, pathology, clinical decision-making, and robotic-assisted surgery, was conducted. AI technologies such as the Da Vinci Surgical Robot and machine learning-based diagnostic tools have significantly improved diagnostic accuracy and the precision of minimally invasive surgeries. AI-driven systems also contributed to better clinical decision support, faster recovery times for patients, and more accurate treatment plans. Overall, AI, through machine learning algorithms and intelligent medical robots, is revolutionizing healthcare by offering promising improvements in diagnostics, surgical precision, and patient care.

Vision-based multi-view reconstruction for high-precision part positioning in industrial robot machining

Traditional industrial robot machining typically involves offline programming of machining trajectories, with part positioning accomplished through robotic tools. However, this method has limitations, particularly when dealing with complex workpieces and dynamic environments. To tackle this problem, this paper introduces a vision-based multi-view reconstruction approach for part positioning in industrial robot machining. Multiple cameras capture multi-view images of the part, reconstruct its 3D point cloud, and match it with the CAD model of the part to achieve high-precision positioning. This method effectively translates offline programmed robot trajectories to real-world scenarios, improving the flexibility and adaptability of robot machining. Experimental results confirm the high accuracy and robustness of the proposed vision-based reconstruction method, achieving a relative error of less than 2 mm for 85.7% of points, with an overall root mean square error of 1.09 mm.

INTEGRATION OF DIGITAL FABRICATION LABORATORIES AND COMPUTATIONAL DESIGN INTO THE ARCHITECTURE CURRICULUM IN TÜRKİYE

The discipline of architecture undergoes transformation practically, cognitively, and pedagogically due to the widespread use of digital design and fabrication technologies in design processes. This paper aims to eluctade the integration of digital fabrication and computational design with architectural design education at undergraduate level. For this purpose, this study examined the undergraduate course contents and spatial conditions of leading universities with digital fabrication laboratories under three headings: digital design, digital fabrication, and spatial reflections. In addition, this research applied semi-structured interviews with the relevant faculty members of three universities that have robotic tools to obtain more detailed information about their pedagogical approaches. According to this study, the curriculum and laboratories are rapidly changing. As a result, architecture departments are expanding their facilities by building laboratories and tools that have the potential for architectural education to fill the gap between practice and theory. However, there are economic limitations to implementing digital fabrication technologies in terms of the tools and materials used by hundreds of students. This research discusses the requirements, potentials, and limitations of theoretical and practical training through digital fabrication tools that should be included in these courses in the curriculum.

Comparing Regularized Logistic Regression and Stochastic Gradient Descent in Predicting Drug-Gene Interactions of Inhibitors of Apoptosis Proteins in Periodontitis.

Periodontitis, characterized by inflammation linked to apoptosis dysregulation, underscores the role of inhibitors of apoptosis proteins (IAPs) like survivin and cIAP1, implicated in disease progression and treatment resistance across various conditions. Our study aims to analyze the prediction of drug-gene interactions by machine learning techniques, combining regularized logistic regression and stochastic gradient descent (SGD) for efficient classification. Data from Probes-Drugs.org on IAP-based drug-protein interactions underwent rigorous annotation and outlier removal. A data robot tool trained machine learning models, regularized logistic regression and SGD (https://app.datarobot.com/new). Network analysis employed Cytoscape to construct and analyze the IAP network, identifying key hub nodes crucial in periodontitis pathogenesis. The constructed IAP network comprised 376 nodes and 556 edges, revealing intricate drug-gene interactions with an average of 2957 neighbors per node. Ten hub nodes were identified as pivotal in regulating biological processes specific to periodontitis, suggesting their potential as therapeutic targets and biomarkers. Predictive models demonstrated high accuracy, with gradient descent achieving 93% and regularized logistic regression achieving 92% in identifying drug-gene interactions within the IAP network. These findings highlight the utility of computational methods in elucidating molecular mechanisms underlying periodontitis, offering insights into potential therapeutic strategies targeting IAP-related pathways. Future research should focus on validating hub genes experimentally and integrating multi-omics data to advance precision medicine approaches in periodontitis treatment.

The single port robotic surgical "toolbox": a primer for beginners.

The aim of this study is to provide a comprehensive overview of the da Vinci Single Port robotic platform, including instruments and tools that can aid in implementing the use of this novel platform. Footage recorded during various Single port robotic urologic procedures and dry labs performed at two US institutions was used as video material. A step-by-step guide illustrating key points on OR set-up, platform, instruments, trocar configurations, intraoperative suctioning, bedside assistance were discussed and highlighted. The Single port surgeon console resembles the Xi console but includes upgraded software. The 6-mm biarticulated instruments incorporate an elbow and a wrist flexible joint. These instruments are deployed through the Access port. Access port kit includes the Access port, and a 25-mm multichannel trocar accommodating an 8-mm flexible scope, and three 6-mm robotic instruments. The 0° endoscope has two sets of articulation: a fixed one, and a distal one, allowing for three movements, selected with a hand command, the "Camera Adjust", the "Camera Control" and the "Relocation." The "Cobra mode," is an extra setting that allows the camera to wing out and move laterally relative to the working instruments. Suction is preferably performed with the Remotely Operated Suction Irrigation system. Herein we provide a detailed guide to the main technical nuances of the Single port platform and a practical overview of the instrumentation that is used during Single port robotic procedures. Knowledge of the toolbox that is used during Single port robotic surgery is key for those approaching for the first time this novel technology.

Characterization of Friction within a Novel 3 mm Wristed Robotic Instrument

Surgical robotic tools are being developed for a variety of surgical procedures that are executed within small workspaces. Novel designs of miniaturized cable-actuated surgical tools for cleft palate repair have previously been developed. However, the behavior and significance of friction within these tools are largely unknown. A study was conducted to investigate the friction in a pulleyless 3 mm diameter wristed instrument. The wrist utilizes cable guide channels that allow for miniaturization at the cost of increased friction. An experimental rig was developed to measure friction within the wrist link mechanism when the tool is positioned at various pitch angles. A strong relationship between the cable tension and the tool’s pitch angle was found as a result of friction. The cable tension increased as the pitch angle approached extreme values (percent increases in the cable tension of 33% and 67.3% at a pitch of 90° and −90°, respectively). However, the resultant cable tension was below the failure strength of the cable, indicating that the design is feasible. The results of this study would be useful to those considering the design of miniature robotic surgical tools that are cable-driven. Significant tool reduction can be achieved by employing static guide channels for the cables, forgoing the use of additional moving components like pulleys while maintaining cable tension well within its break strength. Future work in the design and optimization of novel miniaturized wrist mechanisms should consider frictional effects and their impact on mechanism function.

Enhancing computational thinking in students with autism spectrum disorder and intellectual disabilities: a robot programming approach

Objectives Research examining computational thinking skills development via programming education using robotic teaching tools for students with Autism Spectrum Disorder and Intellectual Disabilities remains limited. This study aims to analyze the advancements in computational thinking skills among middle school students with Autism Spectrum Disorder and Intellectual Disabilities through participation in robot programming classes. Methods Problem-solving proficiency in computational thinking was assessed utilizing Brennan and Resnick’s three dimensions framework. A tailored teaching and learning approach was implemented for robot programming education, accounting for participants’ cognitive abilities and required levels of support. Four middle school students, comprising one with Autism Spectrum Disorder and three with Intellectual Disabilities, were enrolled. Results Significant enhancements were observed in all participants’ computational thinking skills across conceptual understanding, practical application, and perspective. Notably, all participants successfully resolved the final project problem at their individual proficiency levels. The acquisition of computational concepts was found to correlate positively with improved practical computational skills. Additionally, all participants demonstrated keen interest in and positive attitudes toward both robots and programming. Conclusions This study underscores the efficacy of robotic teaching tools in enhancing computational thinking skills through programming education. Additionally, it highlights considerations for enhancing students’ accessibility in future programming class design.

Comparative analysis of semantic segmentation and multi-boosted faster R-CNN for robotic tool detection in diabetes patient care

Diabetes, a common chronic illness, need meticulous patient care and treatment, which frequently necessitates advanced robotic help. The identification of robotic tools is critical in guaranteeing precise and safe medical procedures. With the growing use of robots in healthcare, reliable identification of instruments inside a patient care setting is critical for allowing smooth and efficient medical procedures. We used a Multi-Boosted Faster-Region-based Convolutional Neural Network (MBF-RCNN) to estimate Robotic Tool Detection in Diabetes Patient Care in the present research. Semantic Segmentation is a machine learning methodology centered on classifying pictures pixel-by-pixel, whereas Multi-Boosted Faster R-CNN recognizes objects using a variety of boosting strategies. Decimal Scaling Normalization is used during the preprocessing step to optimize the input data for both procedures. The effectiveness of both approaches is improved by doing extraction of features using Linear Discriminant Analysis (LDA) to find key trends in the information that is provided.The Multi-Boosted Faster-Region-based Convolutional Neural Network (MBF-RCNN) is an improved variation of the Faster R-CNN design that uses the boosting approach to improve object identification performance.Accuracy, Precision, Recall, F1-score, and the Receiver Operating Characteristic (ROC) curve among the assessment metrics used. The findings show that the suggested approaches are effective in identifying and localizing robotic equipment, which is critical for effective treatments in controlling diabetes.This research promotes computer vision applications in healthcare, particularly in the care of diabetic patients. It assesses the efficiency and dependability of Semantic Segmentation and MBF-RCNN for robotic tool identification, opening the way for more efficient and dependable automation for healthcare contexts.

Medical Students Cannot Assess Robotic Surgeons Performing Radical Prostatectomy.

Medical students have previously been shown to be just as effective for video rating as experts. We want to compare medical students to experienced surgeons as video assessors of simulated robot-assisted radical prostatectomy (RARP) performance. Video recordings of three RARP modules on the RobotiX (formerly Simbionix) simulator from a previous study were used. Five novice surgeons, five experienced robotic surgeons, and five experienced robotic surgeons in RARP performed a total of 45 video-recorded procedures. The videos were assessed with the modified Global Evaluative Assessment of Robotic Skills tool as both full-length and an edited edition that only included the first 5 minutes of the procedure. Fifty medical students and two experienced RARP surgeons (ES) performed a total of 680 video ratings of full-length videos and 5-minute videos (2-9 ratings per video). Medical students and ES showed poor agreement for both full-length videos and 5-minute videos (0.29 and -0.13, respectively). Medical students could not discriminate between the skill level of the surgeons in either full-length videos or 5-minute videos ( P = 0.053-0.36 and P = 0.21-0.82), whereas ES could discriminate between novice surgeons and experienced surgeons (full-length, P < 0.001, and 5 minutes, P = 0.007) and intermediate and experienced surgeons (full-length, P = 0.001, and 5 minutes, P = 0.01) in both full-length videos and 5-minute videos. We found that medical students cannot be used to assess RARP because they showed poor agreement with the ES rating for both full-length videos and 5-minute videos. Medical students could not discriminate between surgical skill levels.

Semantic mapping techniques for indoor mobile robots: Review and prospect

With the continuous development of robotics and computer vision technology, mobile robots have been widely applied in various fields. In this process, semantic maps for robots have attracted considerable attention because they provide a comprehensive and anthropomorphic representation of the environment. On the one hand, semantic maps are a tool for robots to depict the environment, which can enhance the robot’s cognitive expression of space and build the communication bond between robots and humans. On the other hand, semantic maps contain spatial location and semantic properties of entities, which helps robots realize intelligent decision-making in human-centered indoor environments. In this paper, we review the primary approaches of semantic mapping proposed over the last few decades, and group them according to the type of information used to extract semantics. First, we give a formal definition of semantic map and describe the techniques of semantic extraction. Then, the characteristics of different solutions are comprehensively analyzed from different perspectives. Finally, the open issues and future trends regarding semantic maps are discussed in detail. We wish this review provides a comprehensive reference for researchers to drive future research in related field.

Acquisition and Development of Scrub Nursing Skills in Robotic-Assisted Cranial and Spinal Neurosurgical Procedures

Introduction. In high-tech operative specialties, including neurosurgery, the rise of interest in robotic systems is observed, since these techniques are hoped to increase the precision of the operation. However, for the optimal implementation of these solutions, the close cooperation between surgeon and perioperative nursing team as well as adequate coordination of their actions is required. These skills needs to be gained and trained. Aim. The following report describes the single center experience of the operating team in launching the robotic navigation in neurosurgical procedures from the vantage point of nursing team. Material and Methods. This work contains a phenomenological analysis of learning process and of optimalisation in cooperating the work of the involved operating team during early phase of introducing the robotic neurosurgical procedures (both cranial and spinal). Here, the typical problems during implementation of these techniques with separate analysis of single steps of preparing and applying the tool sets are described, where critical points and the potential of failure elimination is highlighted. Results. The preparing of the robotic surgical tool set is not demanding and differs only slightly from the preparation of standard sets designed for neuronavigation plus targeted cranial biopsy or percutaneous spine instrumentation, respectively. The key point is to synchronize the actions of the operating surgeon (-s), perioperative nurses and radiologic technicians. Conclusions. Implementation of robotic techniques is a challenge for the whole neurosurgical team, including the scrub/circulating nurses. What is more important in the initial phase than (usually intuitive) operation of the devices, is the coordination of single team members’ actions and developing the communication skills regarding the planned course of the surgery and potential modification of its course, needed before the surgery starts. (JNNN 2024;13(1):29–35)

Robot-assisted stereotactic electroencephalography using 3-dimensional intraoperative imaging and frameless registration tool.

Stereoelectroencephalography (SEEG) is the gold standard to investigate the epileptic network in cases of drug-resistant epilepsy. Robot-assisted SEEG is increasingly being used; however, its installation process in the operating room is more difficult than that of the stereotactic frame procedure. New robotic tools and 3D intraoperative imaging ease the setup while achieving the same mechanical precision and a lower complication rate. In this video, the authors illustrate the surgical technique and step-by-step workflow using a robotic arm (neuromate) guided by a frameless registration system (neurolocate), registered with an intraoperative flat-panel CT scanner (O-arm). The video can be found here: https://stream.cadmore.media/r10.3171/2024.4.FOCVID2419.

РОБОТИЗАЦИЯ ПРОИЗВОДСТВА СЕЛЬСКОХОЗЯЙСТВЕННОЙ ТЕХНИКИ

Increasing labor productivity at agricultural engineering enterprises in modern conditions is impossible without the use of robots, which should replace human labor in technological operations with dangerous and harmful production processes. (Research purpose) The research purpose is evaluating the use of robotics by enterprises of the agricultural machinery industry in the production. (Materials and methods) Conducted an assessment of the use of robotics tools when visiting enterprises in the agricultural engineering industry. (Results and discussion) It has been established that for a sustainable presence and strengthening of their positions in the market, companies producing agricultural machinery are increasing the volume of research and development work on the designs and production technologies of modern machines. It was noted that an increase in labor productivity in modern conditions is impossible without the use of robots, which are designed to replace human labor at work with harmful and dangerous production factors in procurement, when cleaning blanks, with thermal and physical methods of surface treatment of products made of various materials, when painting, as well as in order to reduce defects. It was determined that the use of robotization tools by enterprises of the agricultural machinery industry does not exceed three percent of the total volume of technological operations performed. Robotics tools are used mainly in welding operations. Loading and unloading, replacement of working tools on numerically controlled machines, as well as many other technological operations remain practically not covered. (Conclusions) The conducted studies have shown that machine-building companies have large reserves for using robotics tools in performing technological operations in order to reduce production costs and increase labor productivity. As measures to support the introduction of robots into production, grants are allocated by the Russian Digital Economy and Skolkovo foundations, preferential loans through the industrial development Fund "Digitalization of Industry".

Robotic assessment of patella tracking in total knee arthroplasty

ObjectivesRobotic tools have been developed to improve planning, accuracy and outcomes in total knee arthroplasty (TKA). The purpose of this study was to describe and illustrate a novel technique for assessing the patellofemoral (PFJ) in TKA using an imageless robotic platform. MethodsA consecutive series of 30 R-TKA was undertaken by a single surgeon utilising the described technique. A technique to dynamically assess the PFJ intra-operatively, pre- and post-implantation was developed. A full set of data from 9 cases was then collected and reviewed for analysis. A series of dynamic PFJ tracks collected intra-operatively pre- and post-implantation are presented. Furthermore, a full assessment of PFJ over and under-stuffing through a 90° arc of flexion is illustrated. Finally, a pre- and post-centre of rotation for the PFJ was defined and measured. ResultsThe described technique was defined over a series of 30 R-TKA using the described robotic platform. Nine cases were analysed to determine what data could be measured using the robotic platform. Intra-operative real-time data allowed a visual assessment of PFJ tracking through a range of motion of 0°–90° flexion pre- and post-implantation. PFJ over and under-stuffing was also assessed intra-operatively through a range of motion of 0°–90° flexion. Post-operative analysis allowed a more detailed study to be performed, including defining a pre- and post-implantation centre of rotation (COR) for the patella. Defining the COR allowed the definition of a patella plane. Furthermore, patella mediolateral shift in full extension, and end flexion could be measured. ConclusionIntra-operative assessment of the PFJ in TKA is challenging. Robotic tools have been developed to improve measurement, accuracy of delivery and outcomes in TKA. These tools can be adapted in novel ways to assess the PFJ, which may lead to further refinements in TKA techniques.

Lake Environmental Data Harvester (LED) for Alpine Lake Monitoring with Autonomous Surface Vehicles (ASVs)

This article introduces the Lake Environmental Data Harvester (LED) System, a robotic platform designed for the development of an innovative solution for monitoring remote alpine lakes. LED is intended as the first step in creating portable robotic tools that are lightweight, cost-effective, and highly reliable for monitoring remote water bodies. The LED system is based on the Shallow-Water Autonomous Multipurpose Platform (SWAMP), a groundbreaking Autonomous Surface Vehicle (ASV) originally designed for monitoring wetlands. The objective of LED is to achieve the comprehensive monitoring of remote lakes by outfitting the SWAMP with a suite of sensors, integrating an IoT infrastructure, and adhering to FAIR principles for structured data management. SWAMP’s modular design and open architecture facilitate the easy integration of payloads, while its compact size and construction with a reduced weight ensure portability. Equipped with four azimuth thrusters and a flexible hull structure, SWAMP offers a high degree of maneuverability and position-keeping ability for precise surveys in the shallow waters that are typical of remote lakes. In this project, SWAMP was equipped with a suite of sensors, including a single-beam dual-frequency echosounder, water-quality sensors, a winch for sensor deployment, and AirQino, a low-cost air quality analysis system, along with an RTK-GNSS (Global Navigation Satellite System) receiver for precise positioning. Utilizing commercial off-the-shelf (COTS) components, a Multipurpose Data-Acquisition System forms the basis for an Internet of Things (IoT) infrastructure, enabling data acquisition, storage, and long-range communication. This data-centric system design ensures that acquired variables from both sensors and the robotic platform are structured and managed according to the FAIR principles.

Robot base placement and tool mounting optimization based on capability map for robot-assistant camera holder

Abstract In the field of laparoscopic surgery, research is currently focusing on the development of new robotic systems to assist practitioners in complex operations, improving the precision of their medical gestures. In this context, the performance of these robotic platforms can be conditioned by various factors, such as the robot’s accessibility and dexterity in the task workspace. In this paper, we present a new strategy for improving the kinematic and dynamic performance of a 7-degrees of freedom robot-assisted camera-holder system for laparoscopic surgery. This approach involves the simultaneous optimization of the robot base placement and the laparoscope mounting orientation. To do so, a general robot capability representation approach is implemented in an innovative multiobjective optimization algorithm. The obtained results are first evaluated in simulation and then validated experimentally by comparing the robot’s performances implementing both the existing and the optimized solution. The optimization result led to a 2% improvement in the accessibility index and a 14% enhancement in manipulability. Furthermore, the dynamic performance criteria resulted in a substantial 43% reduction in power consumption.

Advances in the Application of AI Robots in Critical Care: Scoping Review.

In recent epochs, the field of critical medicine has experienced significant advancements due to the integration of artificial intelligence (AI). Specifically, AI robots have evolved from theoretical concepts to being actively implemented in clinical trials and applications. The intensive care unit (ICU), known for its reliance on a vast amount of medical information, presents a promising avenue for the deployment of robotic AI, anticipated to bring substantial improvements to patient care. This review aims to comprehensively summarize the current state of AI robots in the field of critical care by searching for previous studies, developments, and applications of AI robots related to ICU wards. In addition, it seeks to address the ethical challenges arising from their use, including concerns related to safety, patient privacy, responsibility delineation, and cost-benefit analysis. Following the scoping review framework proposed by Arksey and O'Malley and the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we conducted a scoping review to delineate the breadth of research in this field of AI robots in ICU and reported the findings. The literature search was carried out on May 1, 2023, across 3 databases: PubMed, Embase, and the IEEE Xplore Digital Library. Eligible publications were initially screened based on their titles and abstracts. Publications that passed the preliminary screening underwent a comprehensive review. Various research characteristics were extracted, summarized, and analyzed from the final publications. Of the 5908 publications screened, 77 (1.3%) underwent a full review. These studies collectively spanned 21 ICU robotics projects, encompassing their system development and testing, clinical trials, and approval processes. Upon an expert-reviewed classification framework, these were categorized into 5 main types: therapeutic assistance robots, nursing assistance robots, rehabilitation assistance robots, telepresence robots, and logistics and disinfection robots. Most of these are already widely deployed and commercialized in ICUs, although a select few remain under testing. All robotic systems and tools are engineered to deliver more personalized, convenient, and intelligent medical services to patients in the ICU, concurrently aiming to reduce the substantial workload on ICU medical staff and promote therapeutic and care procedures. This review further explored the prevailing challenges, particularly focusing on ethical and safety concerns, proposing viable solutions or methodologies, and illustrating the prospective capabilities and potential of AI-driven robotic technologies in the ICU environment. Ultimately, we foresee a pivotal role for robots in a future scenario of a fully automated continuum from admission to discharge within the ICU. This review highlights the potential of AI robots to transform ICU care by improving patient treatment, support, and rehabilitation processes. However, it also recognizes the ethical complexities and operational challenges that come with their implementation, offering possible solutions for future development and optimization.

AiroTouch: enhancing telerobotic assembly through naturalistic haptic feedback of tool vibrations.

Teleoperation allows workers to safely control powerful construction machines; however, its primary reliance on visual feedback limits the operator's efficiency in situations with stiff contact or poor visibility, hindering its use for assembly of pre-fabricated building components. Reliable, economical, and easy-to-implement haptic feedback could fill this perception gap and facilitate the broader use of robots in construction and other application areas. Thus, we adapted widely available commercial audio equipment to create AiroTouch, a naturalistic haptic feedback system that measures the vibration experienced by each robot tool and enables the operator to feel a scaled version of this vibration in real time. Accurate haptic transmission was achieved by optimizing the positions of the system's off-the-shelf accelerometers and voice-coil actuators. A study was conducted to evaluate how adding this naturalistic type of vibrotactile feedback affects the operator during telerobotic assembly. Thirty participants used a bimanual dexterous teleoperation system (Intuitive da Vinci Si) to build a small rigid structure under three randomly ordered haptic feedback conditions: no vibrations, one-axis vibrations, and summed three-axis vibrations. The results show that users took advantage of both tested versions of the naturalistic haptic feedback after gaining some experience with the task, causing significantly lower vibrations and forces in the second trial. Subjective responses indicate that haptic feedback increased the realism of the interaction and reduced the perceived task duration, task difficulty, and fatigue. As hypothesized, higher haptic feedback gains were chosen by users with larger hands and for the smaller sensed vibrations in the one-axis condition. These results elucidate important details for effective implementation of naturalistic vibrotactile feedback and demonstrate that our accessible audio-based approach could enhance user performance and experience during telerobotic assembly in construction and other application domains.