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    Reports Outline Field Robotics Study Findings from Hunan University (An Improved Inverse Kinematics Solution Method for the Hyper-redundant Manipulator With End -link Pose Constraint)

    48-49页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics - Field Robotics. According to news reporting from Changsha, People's Rep ublic of China, by NewsRx journalists, research stated, "Hyperredundant manipul ators have strong flexibility that benefits from their redundant limb structure. However, a large number of redundant degrees of freedom will also lead the solu tion of inverse kinematics much more difficult, which restricts their motion per formance to some extent." The news correspondents obtained a quote from the research from Hunan University , "Inspired by the FABRIK (Forward and Backward Reaching Inverse Kinematics) met hod, an improved inverse kinematics solution method for the hyper-redundant mani pulator is proposed. Based on the space vector method, the kinematic model of th e manipulator is established to dynamically acquire its endpoint position, and t he workspace is further obtained by using the Monte Carlo method. The original s earch method is optimized, the include angle decoupling mechanism between adjace nt links is established to obtain the rotation angles of each joint, and the joi nt angle limitation is introduced to meet the actual manipulator structural rest riction. On this basis, the pose constraint mechanism is established to realize the control of the end-link pose, and the linear degree of freedom is introduced to realize the solution after the directional expansion of the manipulator's wo rkspace. A series of simulation experiments are carried out. In the experiments, the position error of the manipulator's endpoint is always less than 10-6 mm. M eanwhile, the comparative experimental results show that compared with the origi nal method, the proposed method exhibits higher position accuracy under the cond ition that the computation time is almost the same. In addition, in the end-link pose constraint experiment and path motion experiments, the pose error of the e nd-link is always less than 10-7 degrees, indicating that the end-link pose can also meet the high accuracy requirements under the premise of ensuring high posi tion accuracy."
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    Reports Outline Robotics Findings from Carnegie Mellon University (Towards Auton omous Crop Monitoring: Inserting Sensors In Cluttered Environments)

    49-49页
    查看更多>>摘要：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 out of Pittsburgh, Pennsylvania, by NewsRx editors, research stated, "Monitoring crop nutrients can aid farmers in optimiz ing fertilizer use. Many existing robots rely on vision-based phenotyping, howev er, which can only indirectly estimate nutrient deficiencies once crops have und ergone visible color changes." Financial support for this research came from National Science Foundation (NSF). Our news journalists obtained a quote from the research from Carnegie Mellon Uni versity, "We present a contact-based phenotyping robot platform that can directl y insert nitrate sensors into cornstalks to proactively monitor macronutrient le vels in crops. This task is challenging because inserting such sensors requires sub-centimeter precision in an environment which contains high levels of clutter , lighting variation, and occlusion. To address these challenges, we develop a r obust perception-action pipeline to grasp stalks, and create a custom robot grip per which mechanically aligns the sensor before inserting it into the stalk. Thr ough experimental validation on 48 unique stalks in a cornfield in Iowa, we demo nstrate our platform's capability of detecting a stalk with 94% su ccess, grasping a stalk with 90% success, and inserting a sensor w ith 60% success."
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    New Machine Learning Findings Has Been Reported by Investigators at University o f Sherbrooke (Real-time Torque-distribution for Dual-motor Off-road Vehicle Usin g Machine Learning Approach)

    50-50页
    查看更多>>摘要：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 from Sherbrooke, Canada, by NewsRx correspondents, research stated, "Recently, demand for electri c vehicles (EVs) has increased significantly as people are becoming more conscio us of the environment and the need to reduce carbon emissions. The introduction of multi-motor systems in EVs has brought new challenges in terms of energy effi ciency and performance." Financial support for this research came from Canada Research Chairs. Our news editors obtained a quote from the research from the University of Sherb rooke, "This paper presents a Multi-Ensemble Learning (MEL)-based approach to de sign an Energy Management Strategy (EMS) for a Dual Motor Electric Vehicle (DMEV ) where MEL is a new powerful Machine Learning approach implemented using Python programming language. To make our study concrete, we studied a real DMEV that i s modeled using Energetic Macroscopic Representation and whose control is simula ted using Matlab/Simulink ™ The designed EMS aims to distribute the instant tor que between the two electric motors in an efficient manner, with the objective o f minimizing energy consumption as much as possible. Contrary to existing EMSs, an important advantage of our designed EMS is that it determines the instant tor que distribution in real-time (while the vehicle is running), without knowing in advance how physical parameters (such as the speed and traction force) will evo lve during the current trip."
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    Harbin Institute of Technology Details Findings in Robotics (Placement Optimizat ion of Flexible Proximity Sensors for Human-robot Collaboration)

    51-51页
    查看更多>>摘要：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 originating in Guangdong, People's R epublic of China, by NewsRx journalists, research stated, "Flexible proximity se nsors mounted on robot arms boost obstacle detection in human-robot collaboratio n (HRC). However, most of the flexible sensor placements lack further analysis t o exploit the flexibility, leading to an inefficient and overpriced sensing syst em." 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 Harbin Institute of Technology, "In this letter, we propose a systematic method to optimize the p lacement of the flexible proximity sensor for HRC. To prepare for the optimizati on, the geometric model of a flexible sensor is built and an evaluation metric f or the detection ability is established. Based on a global search algorithm, we obtain the optimized sensor placement with a sufficient detection ability and a minimum number of sensors. An experiment was conducted to verify the reliability of the method. The comparison between the optimized placement results and the c onventional ones indicates that the proposed method could achieve better detecti on performance with much fewer sensors. This method also takes the flexibility i nto account by customizing the placement for different tasks."
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    Singapore General Hospital Reports Findings in Pancreatectomy (Evaluating the ec onomic efficiency of open, laparoscopic, and robotic distal pancreatectomy: an u pdated systematic review and network meta-analysis)

    52-53页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Surgery - Pancreatecto my is the subject of a report. According to news reporting out of Singapore, Sin gapore, by NewsRx editors, research stated, "This study compared the cost-effect iveness of open (ODP), laparoscopic (LDP), and robotic (RDP) distal pancreatecto my (DP). Studies reporting the costs of DP were included in a literature search until August 2023." Our news journalists obtained a quote from the research from Singapore General H ospital, "Bayesian network meta-analysis was conducted, and surface under cumula tive ranking area (SUCRA) values, mean difference (MD), odds ratio (OR), and 95% credible intervals (CrIs) were calculated for outcomes of interest. Cluster anal ysis was performed to examine the similarity and classification of DP approaches into homogeneous clusters. A decision model-based cost-utility analysis was con ducted for the cost-effectiveness analysis of DP strategies. Twenty-six studies with 29,164 patients were included in the analysis. Among the three groups, LDP had the lowest overall costs, while ODP had the highest overall costs (LDP vs. O DP: MD - 3521.36, 95% CrI - 6172.91 to - 1228.59). RDP had the hig hest procedural costs (ODP vs. RDP: MD - 4311.15, 95% CrI - 6005.4 0 to - 2599.16; LDP vs. RDP: MD - 3772.25, 95% CrI - 4989.50 to - 2535.16), but incurred the lowest hospitalization costs. Both LDP (MD - 3663.82, 95% CrI - 6906.52 to - 747.69) and RDP (MD - 6678.42, 95% CrI - 11,434.30 to - 2972.89) had significantly reduced hospitalization costs co mpared to ODP. LDP and RDP demonstrated a superior profile regarding costs-morbi dity, costs-mortality, costs-efficacy, and costs-utility compared to ODP. Compar ed to ODP, LDP and RDP cost $3110 and $817 less per pa tient, resulting in 0.03 and 0.05 additional quality-adjusted life years (QALYs) , respectively, with positive incremental net monetary benefit (NMB). RDP costs $2293 more than LDP with a negative incremental NMB but generates 0 .02 additional QALYs with improved postoperative morbidity and spleen preservati on. Probabilistic sensitivity analysis suggests that LDP and RDP are more cost-e ffective options compared to ODP at various willingness-to-pay thresholds."
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    Study Results from Vardhaman College of Engineering in the Area of Artificial In telligence Published (Patient Satisfaction: The Role of Artificial Intelligence in Healthcare)

    53-54页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on artificial intelligence are presented in a new report. According to news originating from Telangana, Ind ia, by NewsRx correspondents, research stated, "Applications of artificial intel ligence (AI) can be seen in almost every aspect of the healthcare system, as it has potential to affect almost every facet of the healthcare, from detection of ailments and serious or complex chronic diseases to their control, prevention an d cure." The news editors obtained a quote from the research from Vardhaman College of En gineering: "With technological innovations, upgradation and adoption in the fiel d of healthcare, healthcare professionals are required to be well prepared to ac cept the continuously evolving technology and its application to provide best he althcare facilities, which gave rise to the various studies on the role of the m achine learning (ML), AI, deep learning (DL), etc., in the field of healthcare. Similarly, the rise in digitalised hospitals, medical facilities, records and da ta has resulted in the improvisation in the field of healthcare, which in turn h as increased the need of experts, professionals, experienced and digitally liter ate workforce teams in the field of entire healthcare system. Understanding the roles of these advanced technologies, impacts being created on the health, lifes tyle and the entire healthcare system, along with the perception of the patients towards it, will shape the way for the improvements and the applications of AI and its outcomes to be achieved, resulting in healthier world for the patients a nd the society. The objective of the study is to create a patient satisfaction m odel and validate it with respect to factors influencing patient satisfaction of several patients undergoing AI treatment factors. In the study, the United Stat es, Canada, Australia, UAE and China were chosen as a place of survey, as these are advanced countries and the use of AI is highest in these countries compared to other countries, and survey was done with the help of structured questionnair e. In our earlier study, exploratory factor analysis (EFA) was performed for ini tial knowledge development on the construct of patients undergoing AI treatment. "
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    Northeastern University Researchers Describe Findings in Robotics (Controlling t he fold: proprioceptive feedback in a soft origami robot)

    54-54页
    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 new report. According to news reporting from Boston, Massachusetts, by Ne wsRx journalists, research stated, "We demonstrate proprioceptive feedback contr ol of a one degree of freedom soft, pneumatically actuated origami robot and an assembly of two robots into a two degree of freedom system." The news reporters obtained a quote from the research from Northeastern Universi ty: "The base unit of the robot is a 41 mm long, 3-D printed Kresling-inspired s tructure with six sets of sidewall folds and one degree of freedom. Pneumatic ac tuation, provided by negative fluidic pressure, causes the robot to contract. Ca pacitive sensors patterned onto the robot provide position estimation and serve as input to a feedback controller. Using a finite element approach, the electrod e shapes are optimized for sensitivity at larger (more obtuse) fold angles to im prove control across the actuation range. We demonstrate stable position control through discrete-time proportional-integral-derivative (PID) control on a singl e unit Kresling robot via a series of static set points to 17 mm, dynamic set po int stepping, and sinusoidal signal following, with error under 3 mm up to 10 mm contraction. We also demonstrate a two-unit Kresling robot with two degree of f reedom extension and rotation control, which has error of 1.7 mm and 6.1°."
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    Reports Summarize Robotics Study Results from Xiamen University of Technology (D esign of and research on the robot arm recovery grasping system based on machine vision)

    55-56页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-A new study on robotics is now available. Accordi ng to news reporting from Xiamen, People's Republic of China, by NewsRx journali sts, research stated, "With the development of urban modernization, the amount o f generated waste has been constantly increasing, making waste classification ne cessary. In the process of waste bin recycling, the main challenge is improving recycling efficiency and reducing the workload of workers. To address the proble ms of waste bin positioning and retrieval in the waste bin recycling process, th is study proposes an automatic retrieval system based on a combination of machin e vision and robotic arm motion control." Our news correspondents obtained a quote from the research from Xiamen Universit y of Technology: "The main aim is to achieve accurate and efficient detection, r ecognition, and retrieval of different types of waste bins. First, the YOLOv5 de ep learning recognition algorithm is improved using a channel pruning technique to reduce the complexity of the model while ensuring high recognition accuracy, thus facilitating the portability and deployment of the model on various mobile devices. Then, image preprocessing is conducted using the median filtering metho d and the Gamma brightness correction algorithm. The HSV color model is employed , and the H component distribution is used for classifying different types of wa ste bins under different lighting conditions. This allows for image segmentation for different-color waste bins, facilitating the classification and recognition of waste bin images. Finally, the waste bin localization algorithm and robotic arm motion algorithm are employed to accomplish the positioning and retrieval of waste bins. The experimental results indicate that compared to the original YOL Ov5 model, the improved YOLOv5 algorithm can achieve a significant reduction in parameter number, decreasing it from 7,022,326 to 2,828,675, which represents an approximately 60 % decrease. Moreover, with a marginal 0.2 % decrease in accuracy, the FLOPs value decreases from 12.9G to 7.97G, demonstrati ng a reduction of nearly 70 %. The model size is also reduced by al most 60 %. The results indicate that the recognition rates of diffe rent-color waste bins exhibit a trend of initially increasing and then decreasin g with the intensification of light. Among the four colors of waste bins, the re cognition rate of red waste bins is the highest, with an average recognition rat e of 95 %. In contrast, orange waste bins have the lowest average r ecognition rate, with an average value of 91 %. In the grasping exp eriments, the detection and grasping success rates for the red waste bins are th e highest, reaching 95 % and 80 %, respectively."
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    Fudan University Reports Findings in Robotics (Firing feature-driven neural circ uits with scalable memristive neurons for robotic obstacle avoidance)

    56-56页
    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 originating from Shanghai, People's Republic of China, by NewsRx correspondents, research stated, "Neural circuits with specifi c structures and diverse neuronal firing features are the foundation for support ing intelligent tasks in biology and are regarded as the driver for catalyzing n ext-generation artificial intelligence. Emulating neural circuits in hardware un derpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question." Our news journalists obtained a quote from the research from Fudan University, " In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three m emristive Hodgkin-Huxley neurons. The ascending neurons exhibit mixed tonic spik ing and bursting features, which are used for encoding sensing input. Additional ly, we innovatively introduce a selective communication scheme in biology to dec ode mixed firing features using two descending neurons. We proceed to integrate such a neural circuit with a robot for avoidance control and achieve lower laten cy than conventional platforms."
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    Studies from Beijing Union University in the Area of Machine Learning Published (Retrieval of grassland aboveground biomass across three ecoregions in China dur ing the past two decades using satellite remote sensing technology and machine . ..)

    57-57页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New study results on artificial intelligence have been published. According to news reporting from Beijing, People's Republic of China, by NewsRx journalists, research stated, "The aboveground biomass (AGB) is closely linked to the carbon cycle in grassland ecosystems worldwide. Accuratel y quantifying AGB variations is thus essential for assessing grassland carbon se questration and its feedback on climate change." Funders for this research include Beijing Municipal Commission of Education; Bei jing Union University; Beijing Municipal Education Commission; National Natural Science Foundation of China.
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