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检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

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Attention Regulation for Efficient Semantic Segmentation on Unstructured Terrain

Attention Regulation for Efficient Semantic Segmentation on ...

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international conference on Control, automation and Systems ( ICCAS)

作者： Xiujin Liu Feng Xue Xiaoxiao Du Department of Robotics University of Michigan Ann Arbor MI USA

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

We present AR-Net, an efficient semantic segmentation pipeline for unstructured terrains. For applications such as autonomous navigation, it is essential to accurately and efficiently understand the unstructured scenes in outdoor and urban environments. Given RGB images as inputs, the AR-Net uses an encoder backbone to extract multi-scale features and a novel Attention-Regulation layer as part of the decoder to predict the pixel-level segmentation results for unstructured terrains. Our AR-Net model achieved superior segmentation performance and fast inference on two real-world outdoor terrain datasets. We also provide detailed ablation studies and analyses on model parameter selections.

关键词： Analytical models Accuracy Simultaneous localization and mapping Semantic segmentation Urban areas Refining Feature extraction Robustness Regulation Real-time systems

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Model Design and Concept of Operations of Standard Interface for On-orbit Construction

Model Design and Concept of Operations of Standard Interface...

引用

IEEE international conference on robotics and automation (ICRA)

作者： Jingdong Zhao Zirui Wang Ziyi Liu Liangliang Zhao Qifan Duan Hong Liu State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Chang Guang Satellite Technology Co. Ltd. Changchun China Beijing Honor Device Co. Ltd. Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

The construction of large-scale space facilities requires the use of on-orbit construction technology. However, several of its key components, such as standard interface design, compliant control methods, and path planning for multi-branch robots, still need improvement before practical application. This paper presents a comprehensive solution for on-orbit construction tasks, encompassing a novel standard interface, docking control method, and path planning method for space multi-branch robots. Firstly, a novel standard interface is introduced, which features multiple mating modes and a lightweight design. Additionally, a compliant docking method is provided to generate lower contact forces along the Z-direction. Furthermore, for four-armed space robots, a hierarchical planning method is proposed, which innovates in environment map construction and locomotion planning. Specifically, the closed-form Minkowski sum method is employed to solve the robot’s free space, and a concise locomotion method is elucidated based on transition support points. Finally, simulations and experiments are conducted.

关键词： Visualization Machine vision Prototypes Aerospace electronics Path planning Planning Task analysis

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Formation Control of Multiple Underactuated Unmanned Surface Vessel Systems Based on the Leader-Follower Method

Formation Control of Multiple Underactuated Unmanned Surface...

引用

IEEE conference on Cybernetics and Intelligent Systems

作者： Jianyang Yuan Shuzhi Sam Ge Xiaoling Liang Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (数字)9798350364194

ISBN: (纸本)9798350364200

This paper focuses on formation control for multiple underactuated unmanned surface vessels (USVs) system based on the leader-follower method. A new formation control model is first proposed. Then control laws for the kinematics and dynamics parts are developed separately based on the Lyapunov direct method and proportional control. The formation controller guarantees that the fleet can move in the desired structure with stability under disturbances. Numerical simulations are conducted to verify the controller’s effectiveness.

关键词： Proportional control Navigation Random access memory Numerical simulation Formation control Stability analysis Numerical models

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Distributed Variable-Baseline Stereo SLAM from two UAVs

Distributed Variable-Baseline Stereo SLAM from two UAVs

引用

IEEE international conference on robotics and automation (ICRA)

作者： Karrer, Marco Chli, Margarita Swiss Fed Inst Technol Vis Robot Lab Zurich Switzerland

ISBN: (纸本)9781728190778

Visual-Inertial Odometry (VIO) has been widely used and researched to control and aid the automation of navigation of robots especially in the absence of absolute position measurements, such as GPS. However, when the observable landmarks in the scene lie far away, as in highaltitude flights for example, the fidelity of the metric scale estimate in VIO greatly degrades. Aiming to tackle this issue, in this work, we utilize the virtual stereo setup formed by two Unmanned Aerial Vehicles (UAVs), equipped with one camera and one Inertial Measurement Unit (IMU) each, exploiting their view overlap and relative distance measurements between them using onboard Ultra-Wideband (UWB) modules to enable collaborative VIO. In particular, we propose a decentralized collaborative estimation scheme, where each agent holds its own local map, achieving a low pose estimation latency, while ensuring consistency of each agents' estimates via consensus-based optimization. Following a thorough evaluation in photorealistic simulations, we demonstrate the effectiveness of the approach at high-altitude flights of up to 160m, going significantly beyond the capabilities of state-of-the-art VIO methods. Finally, we show the advantage of actively adjusting the baseline on-the-fly over a fixed, target baseline, resulting in a significant reduction of the estimation error. Video - https://***/SdL4Jb- BQ28

关键词： automation Three-dimensional displays Simultaneous localization and mapping Pose estimation Collaboration Cameras Unmanned aerial vehicles

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Analysis of Motor Imagery-Based fNIRS-BCI for Knee Flexion and Extension

Analysis of Motor Imagery-Based fNIRS-BCI for Knee Flexion a...

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international conference on robotics and Artificial Intelligence (ICRAI)

作者： Hamza Shabbir Minhas Hammad Nazeer Noman Naseer Iraj Kainat Haroon Khan Peyman Mirtaheri Department of Mechatronics and Biomedical Engineering Air University Islamabad Pakistan Department of Mechanical Electronic and Chemical Engineering OsloMet - Oslo Metropolitan University Oslo Norway

ISBN: (数字)9798350355703

ISBN: (纸本)9798350355710

This study aimed to explore the potential of functional near-infrared spectroscopy (fNIRS) as a non-invasive technique for detecting hemodynamic responses in cortical brain activities during motor imagery (MI) tasks. Specifically, the study focused on classifying multiclass MI tasks with fNIRS data. A total of 10 healthy individuals participated in the experiment, where they were instructed to perform motor imagery tasks. A multi-channel continuous wave fNIRS system records the signals from the motor cortex for knee flexion and extension imagery tasks. Discriminant Analysis (LDA) and Support Vector Machine (SVM), comparatively computationally efficient, algorithms were used to classify the data for fNIRS-based BCI applications. The SVM classifier performed comparatively better than the LDA classifier in accuracy, with 88.8% and 89.4% for two-feature and three-feature combinations. Brain activation maps show the increased activation for flexion movement of the knee. Future research should focus on refining the classification process through feature selection, preprocessing improvements, and ensemble methods to enhance accuracy.

关键词： Support vector machines Industries Limbs Accuracy Neuromuscular Refining Motors Hemodynamics Functional near-infrared spectroscopy robotics and automation

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Leveraging Large Language models for Enhancing Financial Compliance: A Focus on Anti-Money Laundering Applications

Leveraging Large Language Models for Enhancing Financial Com...

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robotics, automation and Artificial Intelligence (RAAI), IEEE international conference on

作者： Yuqi Yan Tiechuan Hu Wenbo Zhu Olin Business School Washington University in St. Louis Saint Louis MO Department of Computer Science John Hopkins University Baltimore MD Physical Science Division University of Chicago Chicago IL

ISBN: (数字)9798331520038

ISBN: (纸本)9798331520045

Money laundering is dangerous to the world's finan-cial institutions, because it allows hiding illegal cash and supports various criminal activities. Due to reliance on manual procedures and rule-based systems, traditional Anti-Money Laundering (AML) techniques need assistance in managing the complexity and volume of contemporary financial transactions. This research explores how Large Language models (LLMs), such as GPT-3 and BERT, can improve AML by utilizing cutting-edge natural language processing capabilities to provide more reliable and scalable money laundering detection and prevention solutions. By examining the transformational potential of LLMs in overcoming the drawbacks of conventional techniques, the research fills a significant vacuum in the present AML procedures. Enhancing transaction monitoring, refining client due diligence procedures, streamlining sanctions screening, and aiding in the production of precise suspicious activity notifications are among the primary study issues. The main assumption is that utilizing LLMs' capacity to handle unstructured data and spot complex patterns, AML accuracy and efficiency will significantly increase compared to traditional systems. The goals include implementing LLMs across AML functions, assessing their effectiveness with various datasets, as well as presenting empirical research and case studies to prove their superiority. By advancing our knowledge of and ability to use LLMs in financial compliance, this research is expected to strengthen the defenses against financial crimes.

关键词： Large language models Prevention and mitigation Refining Vacuum technology Production Manuals Natural language processing Reliability Robots Monitoring

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Research on Salt Pool Ion Concentration Prediction Model Based on LSTM and Attention Mechanism

Research on Salt Pool Ion Concentration Prediction Model Bas...

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IEEE international conference on Mechatronics, robotics and automation (ICMRA)

作者： Shaocheng Qu Xiaocheng Xiang Haiyang Tang Guohong Yi Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China Center of Technology SDIC Xinjiang Luobupo Hoevellite Co. Ltd Hami China

ISBN: (数字)9798350352474

ISBN: (纸本)9798350352481

The Lop Nur Salt Lake in Xinjiang is rich in underground brine resources and serves as an important potassium fertilizer production area in China. Potassium, an essential nutrient for plant growth, not only improves plant quality but also enhances their resistance to lodging, drought, cold, and lodging, playing a crucial role in agricultural production. In the process of ion collection in Lop Nur Salt Lake, the predicted ion concentration serves as a significant reference for guiding the industrial automation of salt mining machines. The predicted ion concentration is not only a part of automated mining but also a crucial step in the automated separation and purification of potassium salt crystals, as the ion concentration at the collection site directly affects the method of impurity removal. The predicted ion concentration can guide the automated production of potassium salt, and its accuracy directly impacts the efficiency of automated potassium salt production. To improve the accuracy of current salt pond ion concentration predictions and reduce prediction costs, this paper proposes a model integrating LSTM and attention mechanisms for time series prediction. We collected measurement data for various ion concentrations such as K + , Na + , $\text{SO}_4^{2 -}$, Cl − , and Mg 2+ using ion concentration measurement sensors, recording features such as collection time, location coordinates, salt field number, temperature, and air humidity. By training and testing the sample set using different models and evaluating and comparing the experimental results using various performance evaluation metrics, we found that the proposed model can effectively model long time series data, outperforming RNN (Recurrent Neural Network) and CNN (Convolutional Neural Network) in terms of prediction performance.

关键词： Temperature measurement Salt Attention mechanisms Time series analysis Production Predictive models Ions Data models Potassium Long short term memory

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Depth Recognition of Hard Inclusions in Tissue Phantoms for Robotic Palpation

Depth Recognition of Hard Inclusions in Tissue Phantoms for ...

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2022 IEEE international conference on Real-Time Computing and robotics, RCAR 2022

作者： Zhou, Zhenning Fang, Senlin Ye, Chaoxiang Mi, Tingting Huang, Binhua Li, Xiaoyu Yi, Zhengkun Wu, Xinyu Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Shenzhen Institute of Artificial Intelligence and Robotics for Society SIAT Branch Shenzhen518055 China

ISBN: (数字)9781665469838

ISBN: (纸本)9781665469838

Medical palpation is an effective diagnosis method in which physicians use tactile sensation to diagnose a patient's pathology. Robotic palpation is a novel technique that leverages robots to assist medical diagnosis. The problem of tactile information loss in Robot-assisted Minimally Invasive Surgery (RMIS) has limited the development of the robot-assisted surgical system. Meanwhile, surgeons are difficult to acquire some key information about lesions only via visual feedback, such as tumor depth. To address the issue, we propose a tactile perception algorithm on the basis of the CNN-LSTM network, which achieves the depth recognition of hard inclusions in tissue phantoms. The method realizes the classification of twelve depths of hard inclusions. In addition, due to using hypergeometric distribution encoding, the proposed method can exploit the ordinal information of the labels to significantly improve the recognition accuracy rate. The experimental results on 720 real tactile data show that the average recognition rate is 96.45%. Compared with other state-of-the-art methods, the recognition accuracy rate of the proposed algorithm is the highest. © 2022 IEEE.

关键词： Tumors

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Automated Mosquito Salivary Gland Extractor for PfSPZ-based Malaria Vaccine Production

Automated Mosquito Salivary Gland Extractor for PfSPZ-based ...

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IEEE international conference on robotics and automation (ICRA)

作者： Li, Wanze He, Zhuohong Vora, Parth Wang, Yanzhou Vagvolgyi, Balazs Leonard, Simon Goodridge, Anna Iordachita, Iulian Hoffman, Stephen L. Chakravarty, Sumana Taylor, Russell H. Johns Hopkins Univ Lab Computat Sensing & Robot Baltimore MD 21218 USA Sanaria Inc Rockville MD USA

ISBN: (纸本)9781728190778

Malaria is a worldwide scourge, and the broad deployment of an effective vaccine would improve the lives of millions of people. A vaccine based on Plasmodium falciparum (PfSPZ) sporozoites extracted from the salivary glands of infected mosquitoes shows significant promise. However, the large-scale industrial production of PfSPZ-based vaccines will benefit from automation of the key step of extracting sporozoites from mosquito salivary glands that is currently performed by manual microdissection. In this work, we demonstrate a robotic system prototype for extracting salivary glands from mosquitoes to streamline vaccine production and reduce the need for operators. In the proposed system, mosquitoes are decapitated in an automated robotic pick-place-decapitate process, then a squeezer apparatus extracts mosquito salivary glands from the body. Mosquito detection and body part localization are performed by computer vision methods. The software allows system operation in simulation and on the robotic hardware, which facilitates subsystem development and integration. Experiments show encouraging results with success rates of 93% in robotic mosquito manipulation and 87.1% in salivary gland extraction. The system has the potential to improve the efficiency of PfSPZ vaccine production with significant gains in throughput and reduction in training times for a highly deskilled initial manual step. Further, this system is expected to pave the way for a more mature future system.

关键词： Malaria Vaccine Computer Vision Micro-robotics Soft Object automation Modular Control ROS Simulation

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Optimization Design of the Toroidal Worm Wheel Hob for Robotic Joint with Worm Gear Pair Transmission

Optimization Design of the Toroidal Worm Wheel Hob for Robot...

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robotics, Control and automation (ICRCA), international conference on

作者： Zhijiang Chen Chunming Xia Yingfan Ren Chao Zhang Jie Yang Department of Mechanical and Electronic Engineering Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9798331544577

ISBN: (纸本)9798331544584

To improve the transmission efficiency of the toroidal worm gear pairs in robotic joints and to enhance the accuracy of the toroidal worm wheel hob in cutting worm wheels, a method is proposed that involves using cylindrical forming surface milling to create helical grooves on the front face of the toroidal worm wheel hob. Based on the principle of gear meshing, a mathematical model is established for the development of the helical grooves on the front face of the toroidal worm wheel hob using a cylindrical generating surface. The model uses planar second envelopment for the toroidal worm wheel. Additionally, formulas are provided for calculating the rake angles on both sides of the cutting edges in the indexing ring plane. The analysis of the obtained rake angle values reveals that when machining helical chip clearance grooves for variable transmission ratio toroidal worm wheel hobs, the rake angles on both sides of the hob are within ±0.25°. Compared to machining helical chip clearance grooves for fixed transmission ratio toroidal worm wheel hobs, there is a noticeable decrease in the absolute value of the rake angles on both sides of the cutting edges, leading to a significant improvement in cutting conditions. Simulation machining of the helical grooves for the toroidal worm wheel hob was carried out, and the rake angle was measured within the simulation software. The measurement results align with the calculated results, validating the correctness of the method presented in this paper.

关键词： Accuracy Gears Robot kinematics Wheels Machining Mathematical models Mobile robots Software measurement Grippers Faces

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