查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on robotics is now availab le. According to news reporting originating from Niteroi, Brazil, by NewsRx corr espondents, research stated, "This research presents a cooperation strategy for a heterogeneous group of robots that comprises two Unmanned Aerial Vehicles (UAV s) and one Unmanned Ground Vehicles (UGVs) to perform tasks in dynamic scenarios ." Financial supporters for this research include Cefet/rj, The Federal Brazilian R esearch Agencies Capes; Cnpq; Rio De Janeiro Research Agency, Faperj. Our news reporters obtained a quote from the research from Fluminense Federal Un iversity: "This paper defines specific roles for the UAVs and UGV within the fra mework to address challenges like partially known terrains and dynamic obstacles . The UAVs are focused on aerial inspections and mapping, while UGV conducts gro und-level inspections. In addition, the UAVs can return and land at the UGV base , in case of a low battery level, to perform hot swapping so as not to interrupt the inspection process. This research mainly emphasizes developing a robust Cov erage Path Planning (CPP) algorithm that dynamically adapts paths to avoid colli sions and ensure efficient coverage. The Wavefront algorithm was selected for th e two-dimensional offline CPP. All robots must follow a predefined path generate d by the offline CPP." According to the news editors, the research concluded: "The study also integrate s advanced technologies like Neural Networks (NN) and Deep Reinforcement Learnin g (DRL) for adaptive path planning for both robots to enable real-time responses to dynamic obstacles. Extensive simulations using a Robot Operating System (ROS ) and Gazebo platforms were conducted to validate the approach considering speci fic real-world situations, that is, an electrical substation, in order to demons trate its functionality in addressing challenges in dynamic environments and adv ancing the field of autonomous robots."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Robotics have been published. According to news reporting originating from Beijing, People's Republic of China, by NewsRx correspondents, research stated, "In nature, when e ncountering unexpected uncertainty, animals tend to react quickly to ensure safe ty as the top priority, and gradually adapt to it based on recent valuable exper ience. We present a framework, namely EVOLutionary model-based uncertainty obser VER (EVOLVER), to mimic the bio-behavior for robotics to achieve rapid transient reaction ability and high-precision steady-state performance simultaneously." Financial support for this research came from Defense Industrial Technology Deve lopment. Our news editors obtained a quote from the research from Beihang University, "In particular, the Koopman operator is leveraged to explore the latent structure o f internal and external disturbances, which is subsequently utilized in an evolu tionary model-based disturbance observer to estimate the eventual disturbance. T he resulting observer can guarantee a provable convergence in optimal conditions . Several practical considerations, including construction of a training dataset , data noise handling, and lifting functions selection, are elaborated in pursui t of the theoretical optimality in real applications. The lightweight feature of our framework enables online computation, even on a microprocessor (STM32F7 wit h 100 Hz control frequency). The framework is thoroughly evaluated by one simula tion and three experiments. The experimental scenarios include: 1) Trajectory pr ediction of an irregular free-flying object subject to aerodynamic drag, 2) indo or and outdoor agile flights of a quadrotor subject to wind gust, and 3) high-pr ecision end-effector control of a manipulator subject to base moving disturbance ."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Robotics are disc ussed in a new report. According to news reporting from Nanjing, People's Republ ic of China, by NewsRx journalists, research stated, "PurposeStiffness adjusting ability is essential for soft robotic arms to perform complex tasks. A soft sta te enables dexterous operation and safe interaction, while a rigid state enables large force output or heavy weight carrying." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Natural Science Foundation of Jiangsu Province. The news correspondents obtained a quote from the research from Nanjing Tech Uni versity, "However, making a compact integration of soft actuators with powerful stiffness adjusting mechanisms is challenging. This study aims to develop a pist on-like particle jamming mechanism for enhanced stiffness adjustment of a soft r obotic arm has two pairs of differential tendons for spatial bending, and a jamming co re consists of four jamming units with particles sealed inside braided tubes for stiffness adjustment. The jamming core is pushed and pulled smoothly along the tendons by a piston, which is then driven by a motor and a ball screw mechanism. FindingsThe tip displacement of the arm under 150 N jamming force and no more th an 0.3 kg load is minimal. The maximum stiffening ratio measured in the experime nt under 150 N jamming force is up to 6-25 depends on the bending direction and added load of the arm, which is superior to most of the vacuum powered jamming proposed robotic arm makes an innovative compact integration of tendon-driven r obotic arm and motor-driven piston-like particle jamming mechanism."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Artific ial Intelligence. According to news reporting out of Amsterdam, Netherlands, by NewsRx editors, research stated, "The early detection of glaucoma is essential i n preventing visual impairment. Artificial intelligence (AI) can be used to anal yze color fundus photographs (CFPs) in a cost-effective manner, making glaucoma screening more accessible." Financial support for this research came from Eurostars. Our news journalists obtained a quote from the research from the University of A msterdam, "While AI models for glaucoma screening from CFPs have shown promising results in laboratory settings, their performance decreases significantly in re al-world scenarios due to the presence of out-of-distribution and low-quality im ages. To address this issue, we propose the Artificial Intelligence for Robust G laucoma Screening (AIROGS) challenge. This challenge includes a large dataset of around 113,000 images from about 60,000 patients and 500 different screening ce nters, and encourages the development of algorithms that are robust to ungradabl e and unexpected input data. We evaluated solutions from 14 teams in this paper and found that the best teams performed similarly to a set of 20 expert ophthalm ologists and optometrists. The highest-scoring team achieved an area under the r eceiver operating characteristic curve of 0.99 (95% CI: 0.98-0.99) for detecting ungradable images on-the-fly. Additionally, many of the algorithm s showed robust performance when tested on three other publicly available datase ts."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Biomedical Engineering-Bone Cement is the subject of a report. According to news reporting from Hebe i, People's Republic of China, by NewsRx journalists, research stated, "Pelvic f ragility fractures in elderly individuals present significant challenges in orth opedic and geriatric medicine due to reduced bone density and increased frailty associated with aging. This study involved 150 elderly patients with pelvic frag ility fractures." The news correspondents obtained a quote from the research from the Department o f Orthopaedic Surgery, "The patients were divided into two groups, the observati on group (Observation) and the control group (Control), using a random number ta ble. Artificial intelligence, specifically the Tianji Orthopedic Robot, was empl oyed for surgical assistance. The observation group received bone cement reinfor cement along with screw fixation using the robotic system, while the control gro up received conventional screw fixation alone. Follow-up data were collected for one-year post-treatment. The observation group exhibited significantly lower cl inical healing time of fractures and reduced bed rest time compared to the contr ol group. Additionally, the observation group experienced less postoperative pai n at 1 and 3 months, indicating the benefits of bone cement reinforcement. Moreo ver, patients in the observation group demonstrated significantly better functio nal recovery at 1-, 3-, and 6-months post-surgery compared to the control group. "
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on pattern recogniti on and artificial intelligence are discussed in a new report. According to news reporting from Shanghai, People's Republic of China, by NewsRx journalists, rese arch stated, "Medical images are susceptible to noise and artifacts, so denoisin g becomes an essential pre-processing technique for further medical image proces sing stages." The news reporters obtained a quote from the research from University of Shangha i for Science and Technology: "We propose a medical image denoising method based on dual-attention mechanism for generative adversarial networks (GANs). The met hod is based on a GAN model with fused residual structure and introduces a globa l skip-layer connection structure to balance the learning ability of the shallow and deep networks. The generative network uses a residual module containing cha nnel and spatial attention for efficient extraction of CT image features. The me an square error loss and perceptual loss are introduced to construct a composite loss function to optimize the model loss function, which helps to improve the i mage generation effect of the model. Experimental results on the LUNA dataset an d "the 2016 Low-Dose CT Grand Challenge" dataset show that DAGAN achieves the be st results in root mean square error (RMSE), structural similarity (SSIM) and pe ak signal-to-noise ratio (PSNR) when compared to the state-of-the-art methods."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on artificial intell igence are discussed in a new report. According to news reporting from Alexandro upolis, Greece, by NewsRx journalists, research stated, "Introduction:This surve y-based study investigates Greek patients' perceptions and attitudes towards gen eric drugs, aiming to identify factors influencing the acceptance and market pen etration of generics in Greece. Despite the acknowledged cost-saving potential o f generic medication, skepticism among patients remains a barrier to their wides pread adoption." Our news journalists obtained a quote from the research from Democritus Universi ty of Thrace: "Methods:Between February 2017 and June 2021, a mixed-methods appr oach was employed, combining descriptive statistics with advanced machine learni ng models (Logistic Regression, Support Vector Machine, Random Forest, Gradient Boosting, and XGBoost) to analyze responses from 2,617 adult participants. The s tudy focused on optimizing these models through extensive hyperparameter tuning to predict patient willingness to switch to a generic medication. Results:The an alysis revealed healthcare providers as the primary information source about gen erics for patients. Significant differences in perceptions were observed across demographic groups, with machine learning models successfully identifying key pr edictors for the acceptance of generic drugs, including patient knowledge and he althcare professional influence. The Random Forest model demonstrated the highes t accuracy and was selected as the most suitable for this dataset. Discussion:Th e findings underscore the critical role of informed healthcare providers in infl uencing patient attitudes towards generics."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news reporting from Catania, Italy, by NewsRx journa lists, research stated, "This paper describes the stiffness analysis of a module -based shape morphing snake-like robot. Snake-like robots have the characteristi c of adapting to unstructured environments by exploiting their ability to reconf igure their body's shape." The news correspondents obtained a quote from the research from the University o f Catania, "However, the excellent mobility contrasts with the ability to transm it high loads, precluding its application in manufacturing operations. This arti cle presents a hybrid structure based on reconfigurable modules equipped with lo ckable joints. The use of multiple modules in series allows for a large workspac e. Furthermore, the parallel structure of the single modules provides for transf erring or sustaining high loads. First, the reliability and precision of the the oretical model has been verified using finite element analysis (FEA). The relati ve errors are less than 5%. Then, a morphing module has been constr ucted as a physical demonstrator for the kinematic parameters and stiffness para meters used in elastostatic analysis. Finally, a five-segment prototype has been manufactured and tested." According to the news reporters, the research concluded: "There is a deviation b etween the experimental results and the theoretical results due to manufacturing errors of the prototype but the trend of displacement change shown in the exper imental results is basically consistent with the theoretical results." This research has been peer-reviewed.
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating in Istanbu l, Turkey, by NewsRx journalists, research stated, "The study aimed to assess th e efficacy of OpenAI's advanced AI model, ChatGPT, in diagnosing urological cond itions, focusing on kidney stones. A set of 90 structured questions, compliant w ith EAU Guidelines 2023, was curated by seasoned urologists for this investigati on." Financial support for this research came from University of Health Sciences. The news reporters obtained a quote from the research from the University of Hea lth Sciences, "We evaluated ChatGPT's performance based on the accuracy and comp leteness of its responses to two types of questions [binary ( true/false) and descriptive (multiple-choice)], stratified in to difficulty levels: easy, moderate, and complex. Furthermore, we analyzed the model's learning and adaptability capacity by reassessing the initially incorrec t responses after a 2 week interval. The model demonstrated commendable accuracy , correctly answering 80% of binary questions (n:45) and 93.3% of descriptive questions (n:45). The model's performance showed no significant v ariation across different question difficulty levels, with p-values of 0.548 for accuracy and 0.417 for completeness, respectively. Upon reassessment of initial ly 12 incorrect responses (9 binary to 3 descriptive) after two weeks, ChatGPT's accuracy showed substantial improvement. The mean accuracy score significantly increased from 1.58 ? 0.51 to 2.83 ? 0.93 (p = 0.004), underlining the model's a bility to learn and adapt over time. These findings highlight the potential of C hatGPT in urological diagnostics, but also underscore areas requiring enhancemen t, especially in the completeness of responses to complex queries."
查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Robotics is now availab le. According to news reporting originating in Chengdu, People's Republic of Chi na, by NewsRx journalists, research stated, "Achieving high absolute positioning accuracy is crucial for obtaining aspheric optical components with remarkable s urface quality using a robotic smoothing system. Robot kinematic calibration is an effective means of improving absolute positioning accuracy." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from the Chinese Academy o f Sciences, "The calibration algorithms that use gradient direction have been sh own to significantly improve computational efficiency compared to other calibrat ion methods. However, these algorithms usually suffer from gradient degradation or vanishing after several iterations. In particular, the extended Kalman filter depends on the initial covariance matrix, which must be continually adjusted to reasonable values using artificial means. To address this challenge, an adaptiv e residual extended Kalman filter is proposed for robot kinematic calibration. T his method involves using the residual generated from the current iteration to a void gradient degradation or vanishing in the next iteration. An improved butter fly optimization algorithm is also used to adapt the system covariance matrix, t he covariance matrix of system noises, and the covariance matrix of measurement noises of the extended Kalman filter to improve the identification accuracy. Fin ally, the proposed method's feasibility is demonstrated through sufficient calib ration experiments. The method improved the RMSE positioning accuracy from 0.932 8 to 0.4786 mm, a 48.69 % increase from before calibration. The sm oothing compensation experimental results show that the proposed method achieves optical components with excellent surface quality."
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