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检索条件"任意字段=International Conference on Robot Vision and Signal Processing"

共 18158 条记录，以下是1011-1020 订阅

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Active speed and cruise control of the mobile robot based on the analysis of the position of the preceding vehicle 26

Active speed and cruise control of the mobile robot based on...

引用

26th international conference on Methods and Models in Automation and robotics

作者： Kedziora, Olaf Grzejszczak, Tomasz Probierz, Eryka Bartosiak, Natalia Wojnar, Martyna Skowronski, Kamil Galuszka, Adam Silesian Tech Univ Dept Automat Control & Robot Gliwice Poland

ISBN: (数字)9781665468589

ISBN: (纸本)9781665468596;9781665468589

The aim of this study was to implement a vision system on board of a Nvidia Jetson Nano along with a camera, and to implement the Jetracer platform control. To introduce the theoretical background, literature related to image processing, active cruise control, and autonomous vehicles was reviewed. The image processing and vehicle control methods used in this paper are then described. The remainder of the paper focuses on presenting an implementation of the described algorithms. This implementation was used to conduct tests, which show that the image processing methods investigated were sufficient to control the platform. Factors affecting the quality of control have also been described, these include vehicle speed and steering control gains. Comparative time dependencies of speed and steering level were plotted for selected trials, allowing the system delays to be noted.

关键词： Active cruise control Computer vision Image segmentation Mobile robot

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A Novel Framework for Cognitive Load Estimation from Electroencephalogram signals Utilizing Sparse Representation of Brain Connectivity 8th

A Novel Framework for Cognitive Load Estimation from Electro...

引用

8th international conference on Computer vision and Image processing (CVIP)

作者： Pain, Subrata Shome, Aritra Nama, Tutan Samanta, Debasis Sarma, Monalisa IIT Kharagpur Adv Technol Dev Ctr Kharagpur 721302 W Bengal India IIT Kharagpur Dept Comp Sci Kharagpur 721302 W Bengal India IIT Kharagpur Subir Chowdhury Sch Qual & Reliabil Kharagpur 721302 W Bengal India

ISBN: (纸本)9783031581809;9783031581816

Cognitive load is the quantity of mental activity imposed on a user's working memory while performing any cognitive task. As the performance of a human depends on the imposed mental workload, estimating cognitive load is critical for maintaining human efficiency through cognitive monitoring. Recently, cognitive load estimation utilizing the brain signals recorded by Electroencephalogram (EEG) has gained popularity. Traditional EEG signal-based cognitive load detection methods generally focus on extracting temporal and frequency-based features from individual EEG electrodes, thus neglecting dynamic functional relationships between the brain regions. This study proposes a cognitive load estimation framework utilizing the sparse representation of the brain network data. From the multichannel EEG data, brain networks are obtained using functional connectivity measures, and the sparse codes of the same are computed using the Orthogonal Matching Pursuit algorithm. Then a sparse representation-based classifier is developed that utilizes the sparse codes. The proposed framework is implemented on a 3-class cognitive load dataset recorded at IIT Kharagpur, and the model's efficacy is measured through sparse reconstruction error and classification performances.

关键词： Sparse Modelling Brain Network Topology Cognitive Load Electroencephalogram signal processing Sparsity-based Classification

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Integrating HL7 FHIR into Clinical Decision Support Systems: A Real-World Application with Pepper Humanoid robot in Hospital During Doctor Visits 9

Integrating HL7 FHIR into Clinical Decision Support Systems:...

引用

9th international conference on Mathematics and Computers in Sciences and Industry, MCSI 2024

作者： Safran, Valentino Horvat, Samo Ilijevec, Bojan Roj, Igor Rober Flis, Vojko Mlakar, Izidor University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory of Digital Signal Processing Maribor Slovenia University Medical Centre Maribor Department of Thoracic Surgery Maribor Slovenia University Medical Centre Maribor Clinical Department of Abdominal and General Surgery Maribor Slovenia University Medical Centre Maribor Department of Nurses in Clinic for Surgery Maribor Slovenia University Medical Centre Maribor Clinical Department of Cardiac Surgery Maribor Slovenia

ISBN: (纸本)9798350377224

This study explores the integration of HL7 Fast Healthcare Interoperability Resources (FHIR) into a Clinical Decision Support System (CDSS) utilizing a Pepper robot to enhance doctor visits in a hospital setting. We evaluate a real-world implementation where the Pepper robot acts as an interface for data collection from patients, clinical monitors, and hospital information systems. The CDSS leverages FHIR to seamlessly integrate this data and present it visually, aiming to improve clinical decision-making processes for doctors. Our research investigates the potential of this FHIR-based CDSS with a robot interface to optimize healthcare delivery and potentially improve patient outcomes. © 2024 IEEE.

关键词： Anthropomorphic robots

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Chaotic Salp Swarm Algorithm for Inverse Kinematics of a 5-DOF Drill Floor robot 5

Chaotic Salp Swarm Algorithm for Inverse Kinematics of a 5-D...

引用

5th international conference on Intelligent Control, Measurement and signal processing, ICMSP 2023

作者： Zhao, Fang Yang, Shuangye Liu, Jie Wu, Bo Hu, Youmin School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China CNPC National Engineering Research Center for Oil&gas Drilling Equipment Co. Ltd. Baoji China School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350336030

As automation technology continues to advance in the global oil industry, intelligence is becoming a crucial trend. The focus of future research and development will be on reducing labor, minimizing operational risks, and enhancing work efficiency. The kinematics problem of drill floor robots is the basic problem for achieving intelligent operation, and inverse kinematics is the key problem for the kinematics solution. This paper focuses on the inverse kinematics solution of a drill floor robot that does not meet the Piper criteria. A modified Chaotic Salp Swarm Algorithm (MCSSA) is proposed for the robot. The algorithm utilizes Gaussian chaotic maps for population initialization and updates the salp leader positions, imitating the individual positions update mechanism of particle swarm optimization (PSO) to update the salp followers' positions. The improved method is used to calculate inverse kinematics solutions and is compared with classical PSO, Differential Evolution Algorithm (DE), Genetic Algorithm (GA), and Salp Swarm Algorithm (SSA) algorithms. The results show that the improved SSA algorithm performs better for inverse kinematics problems. © 2023 IEEE.

关键词： Particle swarm optimization (PSO)

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WHAT IS THE PATIENT LOOKING AT? ROBUST GAZE-SCENE INTERSECTION UNDER FREE-VIEWING CONDITIONS 47

WHAT IS THE PATIENT LOOKING AT? ROBUST GAZE-SCENE INTERSECTI...

引用

47th IEEE international conference on Acoustics, Speech and signal processing (ICASSP)

作者： Al-Hindawi, Ahmed Vizcaychipi, Marcela P. Demiris, Yiannis Imperial Coll London Personal Robot Lab London England Chelsea & Westminster Hosp NHS Fdn Trust Magill Dept Anaesthesia London England Imperial Coll London Anaesthet Pain Med & Intens Care London England

ISBN: (纸本)9781665405409

Locating the user's gaze in the scene, also known as Point of Regard (PoR) estimation, following gaze regression is important for many downstream tasks. Current techniques either require the user to wear and calibrate instruments, require significant pre-processing of the scene information, or place restrictions on user's head movements. We propose a geometrically inspired algorithm that, despite its simplicity, provides high accuracy and O(J) performance under a variety of challenging situations including sparse depth maps, high noise, and high dynamic parallax between the user and the scene camera. We demonstrate the utility of the proposed algorithm in regressing the PoR from scenes captured in the Intensive Care Unit (ICU) at Chelsea & Westminster Hospital NHS Foundation Trust (a).

关键词： Eye Tracking Point of Regard estimation Gaze Cue estimation

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Integrating Reconfigurable Foot Design, Multi-modal Contact Sensing, and Terrain Classification for Bipedal Locomotion 3

Integrating Reconfigurable Foot Design, Multi-modal Contact ...

引用

3rd Modeling, Estimation and Control conference (MECC)

作者： Tyler, Ted Malhotra, Vaibhav Montague, Adam Zhao, Zhigen Hammond, Frank L., III Zhao, Ye Georgia Inst Technol George W Woodruff Sch Mech Engn Atlanta GA 30309 USA

ISBN: (纸本)9781713872344

The ability of bipedal robots to adapt to diverse and unstructured terrain conditions is crucial for their deployment in real-world environments. To this end, we present a novel, bio-inspired robot foot design with stabilizing tarsal segments and a multifarious sensor suite involving acoustic, capacitive, tactile, temperature, and acceleration sensors. A real-time signal processing and terrain classification system is developed and evaluated. The sensed terrain information is used to control actuated segments of the foot, leading to improved ground contact and stability. The proposed framework highlights the potential of the sensor-integrated adaptive foot for intelligent and adaptive locomotion.

关键词： Mechatronic Systems robotics Modeling Identification and signal processing

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Design and Implementation of Drug Pick-and-place robot for Elderly Service 5

Design and Implementation of Drug Pick-and-place Robot for E...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Diao, Xingyao Huang, Yongming Lin, Ping Hong, Weihang School of Automation Southeast University Jiangsu Nanjing China

ISBN: (纸本)9781510662520

At present, there is a lack of targeted methods for service robots in drug identification and pick-and-place. The traditional visual-based drug identification method often has low recognition accuracy when performing repeated drug identification tasks, and is relatively affected by the shooting angle. To solve these problems, this paper applies digital image processing, radio frequency identification and voice technology and other technologies to propose a drug picking and placing robot system for the elderly. In order to further guarantee the reliability and accuracy of drug identification, this paper takes use of radio frequency information and voice information on the basis of image recognition. In order to achieve real-time and accurate positioning and path planning, this paper uses the information from the host computer and encoder on the basis of using lidar positioning. Experiments such as fixed-point movement and drug grasping test, as well as drug identification test show that the robot system has extremely high reliability and accuracy in drug identification. © 2023 SPIE.

关键词： Mobile robots

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A 3D-CLDNN Based Multiple Data Fusion Framework for Finger Gesture Recognition in Human-robot Interaction 4

A 3D-CLDNN Based Multiple Data Fusion Framework for Finger G...

引用

4th international conference on Control and robotics (ICCR)

作者： Qi, Wen Fan, Haoyu Xu, Yancai Su, Hang Aliverti, Andrea South China Univ Technol Sch Future Technol Guangzhou Peoples R China Chinese Acad Sci Inst Automat Beijing Peoples R China Politecn Milan Dept Elect Informat & Bioengn Milan Italy

ISBN: (纸本)9781665486415

Finger gesture recognition using surface electromyography (sEMG) became an efficient Human-robot Interaction (HRI) solution. Although Machine Learning (ML) techniques are widely applied in this field, the general solutions for labeling and collecting big datasets impose time-consuming implementation and heavy workloads. In this paper, a new deep learning structure, namely three-dimensional convolutional long short-term memory neural networks (3D-CLDNN) for finger gesture identification based on depth vision and sEMG signals, was proposed for human-machine interaction. It automatically labels the depth data by the self-organizing map (SOM) and predicts the hand gesture only adopting sEMG signals. The 3D-CLDNN method is integrated to improve the recognition rate and computational speed. The results showed the highest clustering accuracy (98.60%) and highest accuracy (84.40%) with the lowest computational time compared with different approaches. Finally, real-time human-machine interaction experiments are performed to demonstrate its efficiency.

关键词： Multimodal data fusion Human-robot interaction Deep learning signal processing

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Simulation of vision-based Tactile Sensors with Efficiency-tunable Rendering

Simulation of Vision-based Tactile Sensors with Efficiency-t...

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2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Sun, Yuhao Zhang, Shixin Shan, Jianhua Zhao, Lei Wang, Xiangbo Sun, Fuchun Yang, Yiyong Fang, Bin Anhui University of Technology School of Mechanical Engineering China Tsinghua University Institute for Artificial Intelligence Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Beijing100084 China School of Engineering and Technology Beijing100083 China Hebei University School of Quality and Technology Supervising Baoding China

ISBN: (纸本)9798350325706

vision-based tactile sensors (VBTS) leverages visual modality to present high-resolution tactile information. The vision-based sensing mechanism has good adaptability to robot manipulation because of available information capture and data processing. However, the simulation of VBTS is a challenging problem because it deals with computer graphics and elasto-plastic deformation. In this paper, we propose a simulation approach for VBTS using a rendering approach based on path tracing. The rendering method can be integrated with existing VBTS and robotic simulators for the simulation of robotic systems. In addition, this method can control the rendering efficiency and quality by controlling the number of voxels in the fitting deformation area to meet the requirements of efficient robot training. The experimental results verify that our method can provide high-quality images at low rendering efficiency or reduce image quality to improve rendering efficiency. Our work has the potential to advance the sim-to-real research on VBTS. © 2023 IEEE.

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Unified Keyword Spotting and Audio Tagging on Mobile Devices with Transformers 48

Unified Keyword Spotting and Audio Tagging on Mobile Devices...

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48th IEEE international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Dinkel, Heinrich Wang, Yongqing Yan, Zhiyong Zhang, Junbo Wang, Yujun Xiaomi Corperation Beijing China

ISBN: (纸本)9781728163277

Keyword spotting (KWS) is a core human-machine-interaction front-end task for most modern intelligent assistants. Recently, a unified (UniKW-AT) framework has been proposed that adds additional capabilities in the form of audio tagging (AT) to a KWS model. However, previous work did not consider the real-world deployment of a UniKW-AT model, where factors such as model size and inference speed are more important than performance alone. This work introduces three mobile-device deployable models named Unified Transformers (UiT). Our best model achieves an mAP of 34.09 on Audioset, and an accuracy of 97.76 on the public Google Speech Commands V1 dataset. Further, we benchmark our proposed approaches on four mobile platforms, revealing that the proposed UiT models can achieve a speedup of 2 - 6 times against a competitive MobileNetV2. © 2023 IEEE.

关键词： Audio tagging Keyword spotting vision Transformers weakly supervised learning

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