Zobrazeno 1 - 10
of 177
pro vyhledávání: '"Hu, Kewei"'
Autor:
Pan, Paoqiang, Hu, Kewei, Huang, Xiao, Ying, Wei, Xie, Xiaoxuan, Ma, Yue, Zhang, Naizhong, Kang, Hanwen
Smart Micro Aerial Vehicles (MAVs) have transformed infrastructure inspection by enabling efficient, high-resolution monitoring at various stages of construction, including hard-to-reach areas. Traditional manual operation of drones in GPS-denied env
Externí odkaz:
http://arxiv.org/abs/2408.06030
Autor:
Zhang, Gengming, Cao, Hao, Hu, Kewei, Pan, Yaoqiang, Deng, Yuqin, Wang, Hongjun, Kang, Hanwen
Accurately identifying lychee-picking points in unstructured orchard environments and obtaining their coordinate locations is critical to the success of lychee-picking robots. However, traditional two-dimensional (2D) image-based object detection met
Externí odkaz:
http://arxiv.org/abs/2404.00364
Accurate collection of plant phenotyping is critical to optimising sustainable farming practices in precision agriculture. Traditional phenotyping in controlled laboratory environments, while valuable, falls short in understanding plant growth under
Externí odkaz:
http://arxiv.org/abs/2403.15981
Accurate reconstruction of plant models for phenotyping analysis is critical for optimising sustainable agricultural practices in precision agriculture. Traditional laboratory-based phenotyping, while valuable, falls short of understanding how plants
Externí odkaz:
http://arxiv.org/abs/2402.09685
We present a novel approach for metric dense depth estimation based on the fusion of a single-view image and a sparse, noisy Radar point cloud. The direct fusion of heterogeneous Radar and image data, or their encodings, tends to yield dense depth ma
Externí odkaz:
http://arxiv.org/abs/2401.04325
Autor:
Pan, Naizhong Zhang. Yaoqiang, Jin, Yangwen, Jin, Peiqi, Hu, Kewei, Huang, Xiao, Kang, Hanwen
This work presents an innovative solution for robotic odometry, path planning and exploration in wild unknown environments, focusing on digital modelling. The approach uses a minimum cost formulation with pseudo-randomly generated objectives, integra
Externí odkaz:
http://arxiv.org/abs/2312.17634
Accurate reconstruction of plant phenotypes plays a key role in optimising sustainable farming practices in the field of Precision Agriculture (PA). Currently, optical sensor-based approaches dominate the field, but the need for high-fidelity 3D reco
Externí odkaz:
http://arxiv.org/abs/2311.04154
Agricultural robots must navigate challenging dynamic and semi-structured environments. Recently, environmental modeling using LiDAR-based SLAM has shown promise in providing highly accurate geometry. However, how this chaotic environmental informati
Externí odkaz:
http://arxiv.org/abs/2308.16748
Publikováno v:
2022 TRO
Accurate and reliable sensor calibration is essential to fuse LiDAR and inertial measurements, which are usually available in robotic applications. In this paper, we propose a novel LiDAR-IMU calibration method within the continuous-time batch-optimi
Externí odkaz:
http://arxiv.org/abs/2205.03276
Publikováno v:
In Microelectronics Journal August 2024 150