查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on robotics are presented i n a new report. According to news originating from Wuhan, People's Republic of C hina, by NewsRx correspondents, research stated, "Offline programming (OLP) is a mainstream approach for controlling assembly robots at construction sites." Funders for this research include National Key Research And Development Program of China; China Postdoctoral Science Foundation; National Natural Science Founda tion of China; Key Technologies Research And Development Program. The news editors obtained a quote from the research from Huazhong University of Science and Technology: "However, existing methods are tailored to specific asse mbly tasks and workflows, and thus lack flexibility. Additionally, the emerging large language model (LLM)-based OLP cannot effectively handle the code logic of robot programming. Thus, this paper addresses the question: How can robot contr ol programs be generated effectively and accurately for diverse construction ass embly tasks using LLM techniques? This paper describes a closed user-on-the-loop control framework for construction assembly robots based on LLM techniques. A h ierarchical strategy to generate robot control programs is proposed to logically integrate code generation at high and low levels. Additionally, customized appl ication programming interfaces and a chain of action are combined to enhance the LLM's understanding of assembly action logic. An assembly task set was designed to evaluate the feasibility and reliability of the proposed approach."
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Robotic s. According to news originating from Sorocaba, Brazil, by NewsRx correspondents , research stated, "Evolution has shown that legged locomotion is most adequate for tasks requiring versatile movement on land, allowing animals to traverse a w ide variety of environments ranging from natural terrain to artificial, man-made landscapes with great ease. By employing well-designed control schemes, this ab ility could be replicated for legged robots, enabling them to be used in critica l situations that still pose great danger to human integrity, such as search and rescue missions, inspection of hazardous areas, and even space exploration." Our news journalists obtained a quote from the research from Sao Paulo State Uni versity (UNESP), "This work characterizes the quadruped robot and contact dynami cs that will compose our in-house simulator to be used for prototyping locomotio n control schemes applied to quadruped robots. The proposed simulator computes t he robot dynamics using the Recursive Newton-Euler and Composite-Rigid- Body algo rithms with a few modifications to make certain aspects relevant for contact det ection and control more easily accessible; furthermore, a compliant contact forc e method alongside stick-slip friction modeled the contact dynamics. To allow th e robot to move, a simple PD-independent joint controller was implemented to tra ck a desired leg trajectory. With the same robot and controller implemented usin g the MuJoCo simulation software, this work evaluates the proposed simulator by comparing characteristic locomotion signals such as the trunk pose and the groun d reaction forces. Results showed similar behavior for both simulators, especial ly with regard to the contact detection, despite the significantly different con tact models."
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating in Beijing, Peopl e's Republic of China, by NewsRx journalists, research stated, "Synthesis of fun ctional nanostructures with the least number of tests is paramount towards the p ropelling materials development. However, the synthesis method containing multiv ariable leads to high uncertainty, exhaustive attempts, and exorbitant manpower costs." Funders for this research include Beijing National Science Foundation, Military Health Care Project, National Natural Science Foundation of China (NSFC).
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Robotics. According to news reporting originating from Chengdu, People's Republi c of China, by NewsRx correspondents, research stated, "Propeller-based reconfig urable magnetic coupling thrusters are a promising propulsion system for underwa ter robots, due to their vectored thrust and watertightness. This paper presents a lightweight and compact 3-DOF spherical reconfigurable magnetic coupling thru ster (SRMCT-II), and focuses on its thruster configuration and control allocatio n, considering its intrinsic characteristics." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), General Program of Science and Technology Department of Sich uan Province, China, Program of Chengdu Municipal Science and Technology Bureau, China.
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on Artificial Intelligence is now ava ilable. According to news reporting originating in Andhra Pradesh, India, by New sRx journalists, research stated, "Development of a rapid sensors for detecting volatile organic compounds (VOCs) is a need of the hour to effectively mitigate the adverse effect of VOCs on environmental pollution. In this line, the current paper presents the design and development of a non-invasive split-ring resonato r (SRR)-based microwave sensor for detecting liquid VOCs, specifically isopropyl alcohol (IPA), acetone, ethanol, and methanol." The news reporters obtained a quote from the research from the National Institut e of Technology, "Artificial intelligence (AI) based algorithms are gaining popu larity in developing a highly-selective sensor circuit. In the proposed sensor, the SRR circuit is optimized for better detection sensitivity and the multi reso nant behavior of the circuit offers adequate selectivity. The designed sensor of fers better re-usability and thereby supporting AI-based algorithms for continuo us monitoring of VOCs in real-time. Transmission coefficient (S21) S 21 ) of the sensor is measured over the frequency range of 0.8-6 GHz for different VOCs wit h varying concentrations. Analysis of variance (ANOVA) and post hoc Tukey tests are employed to discern significant variations in the measured data. Principle c omponent analysis (PCA) and discriminant analysis are performed over the measure d data to classify the VOCs."
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning - Computational Intelligence are discussed in a new report. According to news re porting out of Moscow, Idaho, by NewsRx editors, research stated, "Large languag e models (LLMs) continue to be adopted for a multitude of previously manual task s, with code generation as a prominent use. Multiple commercial models have seen wide adoption due to the accessible nature of the interface." Our news journalists obtained a quote from the research from the University of I daho, "Simple prompts can lead to working solutions that save developers time. H owever, the generated code has a significant challenge with maintaining security . There are no guarantees on code safety, and LLM responses can readily include known weaknesses. To address this concern, our research examines different promp t types for shaping responses from code generation tasks to produce safer output s. The top set of common weaknesses is generated through unconditioned prompts t o create vulnerable code across multiple commercial LLMs. These inputs are then paired with different contexts, roles, and identification prompts intended to im prove security. Our findings show that the inclusion of appropriate guidance red uces vulnerabilities in generated code, with the choice of model having the most significant effect."
查看更多>>摘要：2024 OCT 03 (NewsRx)-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 Shanghai, People's Republic of China, by NewsRx correspondents, research stated, "The generation o f optimal reference trajectories poses a challenging problem for industrial mach ines due to the trade-off between execution speed and vibration amplitude. This paper presents a novel method for systematically planning smooth and robust S-cu rve trajectories of arbitrary order adapted to vibratory behaviour for high-spee d operations." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), China Postdoctoral Science Foundation.
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Robotics are presented i n a new report. According to news reporting from Chongqing, People's Republic of China, by NewsRx journalists, research stated, "Construction robots, as a colle ction of multidisciplinary technologies, have been extensively studied and imple mented by scholars and engineers to boost construction efficiency and minimize t he reliance on manual labor. However, the practical application of construction robots has been limited due to a lack of systematic research." Financial support for this research came from Science Foundation.
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Data detailed on Machine Learning have been presented. According to news reporting from Ostrava, Czech Republic, by Ne wsRx journalists, research stated, "This paper delves into the cuttingedge appl ications of Machine Learning (ML) within modern Additive Manufacturing (AM), emp loying bibliometric analysis as its methodology. Formulated around three pivotal research questions, the study navigates through the current landscape of the re search field." Funders for this research include European Union under the REFRESH - Research Ex cellence For REgion Sustainability and High-tech Industries, Structural Funds of European Union project. The news correspondents obtained a quote from the research from the Faculty of M echanical Engineering, "Utilizing data sourced from Web of Science, the paper co nducts a comprehensive statistical and visual analysis to unveil underlying patt erns within the existing literature. Each category of ML techniques is elucidate d alongside its specific applications, providing researchers with a holistic ove rview of the research terrain and serving as a practical checklist for those see king to address particular challenges. Culminating in a vision for the Smart Add itive Manufacturing Factory (SAMF), the paper envisions seamless integration of reviewed ML techniques."
查看更多>>摘要：2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Learn ing have been published. According to news reporting originating from Blacksburg , Virginia, by NewsRx correspondents, research stated, "In the world of computat ional materials science, the knowledge of microstructure is vital in understandi ng the process-microstructure-property linkage across various length-scales. To circumvent costly experimental characterizations, typically, analyses on ensembl es of 3D microstructures within a numerical framework are preferred." Financial supporters for this research include NASA's Physical Sciences Research Program, Penn State Institute for Computational and Data Sciences RISE Seed Gra nt, Air Force Office of Scientific Research (AFOSR), Air Force Office of Scienti fic Research (AFOSR), NSF CMMI award. Our news editors obtained a quote from the research from Virginia Polytechnic In stitute and State University (Virginia Tech), "Utilizing a moment invariants-bas ed physical descriptor, the current work quantifies the variations in the micros tructural topology of 3D synthetic data of polycrystalline materials. For the fi rst time, the validation of synthetic microstructures based on two unique AI-bas ed reconstruction approaches was compared, providing valuable insights into the diverse characteristics of each methodology. Virtual 3D microstructure volumes o f forged Ti-7Al and additively manufactured 316L stainless steel alloys were gen erated from 2D experimental data using two methods - Markov Random Field (MRF) a nd deep learning-based volumetric texture synthesis. Quantitative evaluation and validation of the reconstructed volumes were carried out with the aid of moment invariants by comparing local features associated with grain-level properties, such as grain size and shape. The normalized central moments previously employed to compare 2D grain topology were expanded to 3D."
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