IET Cybersystems and Robotics最新文献_第5页

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-25

引用次数: 0

An Immersive Virtual Reality Bimanual Telerobotic System With Haptic Feedback 一种具有触觉反馈的沉浸式虚拟现实双手遥控机器人系统

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-25 DOI: 10.1049/csy2.70033

Han Xu, Mingqi Chen, Gaofeng Li, Lei Wei, Shichi Peng, Haoliang Xu, ZunRan Wang, Huibin Cao, Qiang Li

引用次数: 0

Virtual Reality Integrated Human–Computer Interaction System Based on Ultraleap 3Di Hand Gestures Recognition 基于超跳3Di手势识别的虚拟现实集成人机交互系统

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-22 DOI: 10.1049/csy2.70035

Chujie He, Xiangyu Zhou, Jiarui Zhang, Jing Luo, Yahong Chen, Xiaoli Liu, Shifeng Ma, Junjie Sun

{"title":"Virtual Reality Integrated Human–Computer Interaction System Based on Ultraleap 3Di Hand Gestures Recognition","authors":"Chujie He, Xiangyu Zhou, Jiarui Zhang, Jing Luo, Yahong Chen, Xiaoli Liu, Shifeng Ma, Junjie Sun","doi":"10.1049/csy2.70035","DOIUrl":"10.1049/csy2.70035","url":null,"abstract":"Gesture recognition is a key task in the field of human–computer interaction (HCI). To solve the problems of low accuracy and poor real-time performance in the recognition process, this paper designs a HCI system based on gesture recognition. This paper utilises the Ultraleap 3Di to collect the dynamic gesture dataset for the defined interaction gestures, and the high-precision device guarantees data collection. This paper constructs a framework incorporating the advantages of convolutional neural networks (CNNs) and long short-term memory networks (LSTM) using noncontact gesture interaction as the medium of human–computer collaboration. The framework utilises CNN to perform feature extraction on the input frame information. Then, the extracted feature sequences are fed into LSTM to process the timing information, which is very effective in classifying and recognising the defined dynamic gestures. Finally, a HCI system based on gesture recognition is designed. Based on the Unity3D platform, the UR5 robotic arm was modelled and the cyclic coordinate descent (CCD) algorithm was applied to solve the inverse kinematics, successfully realising the semantic control of gestures on the UR5 robotic arm. The experiment verifies that the CNN–LSTM network can ensure the real-time performance of the whole system and the effectiveness and reliability of the gesture interaction system based on Ultraleap 3Di.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"7 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.70035","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145572622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-22

引用次数: 0

Self-Supervised Anomaly Detection for Substation Equipment With Realistic Diffusion-Based Synthesis and Adaptive Feature Refinement 基于现实扩散综合和自适应特征细化的变电站设备自监督异常检测

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-21 DOI: 10.1049/csy2.70032

Bo Xu, Jia Liu

引用次数: 0

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-21

引用次数: 0

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-19

引用次数: 0

GPS-Denied LiDAR-Based SLAM—A Survey 拒绝gps的激光雷达SLAM-A调查

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-19 DOI: 10.1049/csy2.70031

Haolong Jiang, Yikun Cheng, Weichen Dai, Wenbin Wan, Qinyao Liu, Fanxin Wang

{"title":"GPS-Denied LiDAR-Based SLAM—A Survey","authors":"Haolong Jiang, Yikun Cheng, Weichen Dai, Wenbin Wan, Qinyao Liu, Fanxin Wang","doi":"10.1049/csy2.70031","DOIUrl":"10.1049/csy2.70031","url":null,"abstract":"In recent years, significant advancements have been made in enabling intelligent unmanned agents to achieve autonomous navigation and positioning within large-scale indoor or underground environments. Central to these achievements is simultaneous localization and mapping (SLAM) technology. Concurrently, the rapid evolution of LiDAR technologies has revolutionised SLAM, enhancing localisation and mapping capabilities in extreme environments characterised by high dynamics, sparse features or GPS-denied environment. Although much research has concentrated on camera-based SLAM or GPS-fused SLAM, this paper provides a comprehensive review of the development of LiDAR-based multi-sensor fusion SLAM with a particular emphasis on GPS-denied environments and filter-based sensor fusion techniques. The paper is structured as follows: The first section introduces the relevant hardware and datasets. The second section delves into the localisation methodologies employed. The third section discusses the mapping processes involved. The fourth section addresses open problems and suggests future research directions. Overall, this review aims to offer a thorough analysis of the development trends in SLAM with a focus on LiDAR-based methods, covering both hardware and software aspects, providing readers with a clear reference on workflow for engineering deliverable technologies that can be adapted to various application scenarios.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"7 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.70031","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145572483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive Obstacle Avoidance Using Vision-Based Dynamic Prediction and Strategic Motion Planning 基于视觉的动态预测和策略运动规划的自适应避障

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-19 DOI: 10.1049/csy2.70034

Jianhang Shang, Guoliang Liu, Tenglong Zhang, Haoyang He, Guohui Tian, Wei Li, Zhenhua Liu

{"title":"Adaptive Obstacle Avoidance Using Vision-Based Dynamic Prediction and Strategic Motion Planning","authors":"Jianhang Shang, Guoliang Liu, Tenglong Zhang, Haoyang He, Guohui Tian, Wei Li, Zhenhua Liu","doi":"10.1049/csy2.70034","DOIUrl":"10.1049/csy2.70034","url":null,"abstract":"In human–robot collaboration, ensuring both safety and efficiency in obstacle avoidance remains a critical challenge. This paper proposes a sampling-based danger-aware artificial potential field (SDAPF) method for obstacle avoidance during human–robot collaboration and interaction. Existing methods often struggle with dynamic obstacles and varying environmental complexities, which can hinder their performance. To address these challenges, SDAPF integrates three key components: position sampling for local minimum avoidance, a novel hazard index that quantifies risk based on the distance and relative velocity between the robot and dynamic obstacles and a dynamic obstacle motion prediction module leveraging depth image data. These features enable intelligent path selection, adaptive step size adjustments based on obstacle dynamics and proactive decision-making for collision-free navigation. The hazard index allows the robot to dynamically assess the urgency of avoiding an obstacle, whereas the motion prediction module anticipates future positions of moving obstacles, enabling the robot to plan paths in advance. The effectiveness of SDAPF is demonstrated through both simulations and real-world experiments, highlighting its potential to significantly enhance safety and operational efficiency in complex human–robot interaction scenarios.","PeriodicalId":34110,"journal":{"name":"IET Cybersystems and Robotics","volume":"7 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2025-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/csy2.70034","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145572454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

IF 1.2

IET Cybersystems and Robotics Pub Date : 2025-11-19

引用次数: 0