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SocialVis: Dynamic Social Visualization in Dense Scenes via Real-time Multi-Object Tracking and Proximity Graph Construction 期刊论文
Computer Animation and Virtual Worlds, 2024, 卷号: 35, 期号: 3, 页码: 1-15
作者:  Li BW(李博文);  Li W(李巍);  Wang JQ(王镜淇);  Meng WL(孟维亮);  Zhang JG(张吉光);  Zhang XP(张晓鹏)
Adobe PDF(2914Kb)  |  收藏  |  浏览/下载：43/7  |  提交时间：2024/06/04
dense pedestrian  detection  multi-object tracking  proximity graph  visualization  
Hierarchical Distribution-Based Tightly-Coupled LiDAR Inertial Odometry 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2024, 卷号: 9, 期号: 1, 页码: 1423-1435
作者:  Wang, Chengpeng;  Cao, Zhiqiang;  Li, Jianjie;  Yu, Junzhi;  Wang, Shuo
Adobe PDF(3553Kb)  |  收藏  |  浏览/下载：54/14  |  提交时间：2024/05/28
3D LiDAR inertial odometry,  distribution  filtering  optimization  point cloud constraint degeneration  
Bionic Underwater Vehicle: A Data-Driven Disturbance Rejection Control Framework 期刊论文
IEEE ROBOTICS & AUTOMATION MAGAZINE, 2023, 卷号: 31, 期号: 1, 页码: 18-28
作者:  Wang, Kaihui;  Zou, Wei;  Ma, Ruichen;  Lv, Jiaqi;  Su, Hu;  Wang, Yu;  Ma, Hongxuan
Adobe PDF(2970Kb)  |  收藏  |  浏览/下载：85/11  |  提交时间：2024/02/22
Vehicle dynamics  Robots  Propulsion  Predictive models  Biological system modeling  Robustness  Disturbance observers  
Multi-Correlation Siamese Transformer Network With Dense Connection for 3D Single Object Tracking 期刊论文
IEEE ROBOTICS AND AUTOMATION LETTERS, 2023, 卷号: 8, 期号: 12, 页码: 8066-8073
作者:  Feng, Shihao;  Liang, Pengpeng;  Gao, Jin;  Cheng, Erkang
Adobe PDF(2745Kb)  |  收藏  |  浏览/下载：130/9  |  提交时间：2023/12/21
3D object tracking  Point cloud  Transformer  
Model Predictive Trajectory Tracking Control of an Underactuated Bionic Underwater Vehicle 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2023, 页码: 12
作者:  Wang, Kaihui;  Zou, Wei;  Ma, Ruichen;  Wang, Yu;  Su, Hu
Adobe PDF(4065Kb)  |  收藏  |  浏览/下载：137/16  |  提交时间：2023/11/16
Bionic underwater vehicle (BUV)  model predictive control (MPC)  trajectory tracking  undulatory propulsion  
A Collision-Free Planning and Control Framework for a Biomimetic Underwater Vehicle in Dynamic Environments 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2023, 卷号: 28, 期号: 3, 页码: 1415 - 1424
作者:  Lv, Jiaqi;  Wang, Yu;  Wang, Shuo;  Bai, Xuejian;  Wang, Rui;  Tan, Min
Adobe PDF(3810Kb)  |  收藏  |  浏览/下载：391/82  |  提交时间：2023/02/22
Arctangent nonsingularity terminal sliding mode (ANTSM) control  biomimetic underwater vehicle (BUV)  collision-free in dynamic environments  fuzzy artificial potential field (FAPF) planning  robots  
Narrowing the Gap: Improved Detector Training With Noisy Location Annotations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6369-6380
作者:  Wang, Shaoru;  Gao, Jin;  Li, Bing;  Hu, Weiming
Adobe PDF(1489Kb)  |  收藏  |  浏览/下载：281/37  |  提交时间：2022/11/14
Annotations  Noise measurement  Detectors  Task analysis  Training  Object detection  Degradation  Object detection  noisy label  Bayesian estimation  teacher-student learning  
Cross stage partial connections based weighted Bi-directional feature pyramid and enhanced spatial transformation network for robust object detection 期刊论文
NEUROCOMPUTING, 2022, 卷号: 513, 页码: 70-82
作者:  Lu, Yan-Feng;  Yu, Qian;  Gao, Jing-Wen;  Li, Yi;  Zou, Jun-Cheng;  Qiao, Hong
Adobe PDF(3025Kb)  |  收藏  |  浏览/下载：266/11  |  提交时间：2022/11/14
Robust object detection  Structural deformation  Image detection  Spatial transformation  
Learning to Assemble Noncylindrical Parts Using Trajectory Learning and Force Tracking 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2021, 页码: 12
作者:  Su, Jianhua;  Meng, Yan;  Wang, Lili;  Yang, Xu
Adobe PDF(4865Kb)  |  收藏  |  浏览/下载：370/64  |  提交时间：2022/01/27
Force  Trajectory  Robots  Task analysis  Hidden Markov models  Impedance  Training  Assembly skill  impedance control  learning from demonstration  movement primitives (MPs)  
Visual affordance detection using an efficient attention convolutional neural network 期刊论文
NEUROCOMPUTING, 2021, 卷号: 440, 期号: 2021, 页码: 36-44
作者:  Gu, Qipeng;  Su, Jianhua;  Yuan, Lei
Adobe PDF(1561Kb)  |  收藏  |  浏览/下载：370/76  |  提交时间：2021/06/15
Affordance detection  Attention mechanism  Up-sampling layer