Results 91 to 100 of about 6,523,468 (262)

Masked Autoencoders in 3D Point Cloud Representation Learning

, 2023
Masked Autoencoders in 3D Point Cloud Representation ...
Richard Dazaley (17286946), Xuequan Lu (2318185), Meili Wang (217037), Jincen Jiang (17286943), Lizhi Zhao (1816030)   +4 more
core  

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Semantic Segmentation of Heavy Construction Equipment Based on Point Cloud Data

Buildings
Most of the currently developed 3D point cloud data-based object recognition algorithms have been designed for small indoor objects, posing challenges when applied to large-scale 3D point cloud data in outdoor construction sites.
Suyeul Park, Seok Kim
doaj   +1 more source

Gait Analysis of Pak Biawak: A Necrobot Lizard Built using the Skeleton of an Asian Water Monitor (Varanus Salvator)

Advanced Robotics Research, EarlyView.
Pak Biawak, a necrobot, embodies an unusual fusion of biology and robotics. Designed to repurpose natural structures after death, it challenges conventional boundaries between nature and engineering. Its movements are precise yet unsettling, raising questions about sustainability, ethics, and the untapped potential of biointegrated machines.
Leo Foulds, Donan Satria Yudha, Parvez Alam   +2 more
wiley   +1 more source

Point Cloud Quality Assessment Based on Cross-Modal De-Redundancy

IEEE Access
3D point cloud has been widely applied in multimedia field, such as virtual reality, smart city and etc. However, during the process of 3D point cloud acquisition, storage and transmission, lots of noises will be introduced, leading to degraded visual ...
Xiaoying Ding, Bin Luo, Hanjiang Xiong, Dawei Jin, Jun Wan, Li Jiang   +5 more
doaj   +1 more source

Three different examples of 3D point cloud representation.

, 2016
Three different examples of 3D point cloud representation.
Julie R. Korenberg (159413), Feng Yang (132135), Edward W. Hsu (2503195), Chang-yu Sun (2503189), Chun-yu Chu (2503192), Wan-yu Liu (2503186), Yue-min Zhu (2503183)   +6 more
core   +1 more source

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

Global Context Aware Convolutions for 3D Point Cloud Understanding

, 2020
Recent advances in deep learning for 3D point clouds have shown great promises in scene understanding tasks thanks to the introduction of convolution operators to consume 3D point clouds directly in a neural network. Point cloud data, however, could have
Yibin Tian, Chen, Wei, Zhang, Zhiyuan, Hua, Binh Son, Yeung, Sai Kit, Zhiyuan Zhang, Wei Chen, Sai-Kit Yeung, HUA, Binh-Son, YEUNG, Sai-Kit, Binh-Son Hua, Tian, Yibin   +11 more
core   +1 more source

Reproducing cloud microphysical and irradiance measurements using three 3D cloud generators [PDF]

, 2007
Using three cloud generators, three-dimensional (3D) cloud fields are reproduced from microphysical cloud data measured in situ by aircraft. The generated cloud fields are used as input to a 3D radiative transfer model to calculate the corresponding ...
Ronald Scheirer, Victor Venema, Manfred Wendisch, Francesca Di Giuseppe, Pilewskie, Peter, K Sebastian Schmidt, Schmidt, Sebastian, Di Giuseppe, Francesca, Venema, Victor, Peter Pilewskie, Wendisch, Manfred, Scheirer, Ronald   +11 more
core   +1 more source

Multilevel Embedding and Dropout for Improved 3D Object Detection in Autonomous Driving Systems

Advanced Robotics Research, EarlyView.
A plug‐in framework for RoI‐based 3D object detectors exploits previously untapped multi‐level information within RoI features. Its novel multi‐level embedding and dropout strategy enables the detection head to generate predictions at different feature levels.
Xiaohu Lu, Hayder Radha
wiley   +1 more source