Article
Geography, Physical
Patrick Huebner, Martin Weinmann, Sven Wursthorn, Stefan Hinz
Summary: This paper proposes a fully automatic, voxel-based indoor reconstruction approach to derive semantically-enriched and geometrically completed indoor models from unstructured triangle meshes. The approach does not rely on planar room surfaces or distinct floor levels, and is able to handle challenging indoor environments with curved room surfaces and complex vertical room layouts.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Remote Sensing
Senyuan Wang, Xinyi Liu, Yongjun Zhang, Jonathan Li, Siyuan Zou, Jipeng Wu, Chuang Tao, Quan Liu, Guorong Cai
Summary: We propose a semantic-guided building reconstruction method called SGR, which can achieve independent and complete reconstruction of building models. The method consists of two key stages: 2.5D convex cell complex representation for space partition and semantic-guided graph-cut formulation to eliminate interference. Experimental results show that SGR can authentically reconstruct weakly observed surfaces and obtain watertight models considering fidelity, integrity, and time complexity.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Mathematics, Applied
Jan Groselj, Mario Kapl, Marjeta Knez, Thomas Takacs, Vito Vitrih
Summary: This paper investigates the space of isogeometric spline functions over mixed triangle and quadrilateral meshes, with a focus on planar mixed meshes parameterized by (bi-)quadratic geometry mappings. Theoretical framework for analyzing smoothness conditions and several examples are presented.
APPLIED MATHEMATICS AND COMPUTATION
(2024)
Article
Chemistry, Multidisciplinary
Hanna Sopha, Adelia Kashimbetova, Ludek Hromadko, Ivan Saldan, Ladislav Celko, Edgar B. Montufar, Jan M. Macak
Summary: In this study, large 3D Ti meshes were fabricated by direct ink writing and wirelessly anodized for the first time to prepare highly photocatalytically active TiO2 nanotube layers. The TNT layers with nanotube diameters of up to 110 nm and thicknesses of up to 3.3 μm showed superior performance for the photocatalytic degradation of methylene blue.
Article
Computer Science, Software Engineering
Xue Jiao, Yonggang Chen, Xiaohui Yang
Summary: The superior performance of deep learning in various domains has generated significant interest in its applicability to 3D computer graphics. However, learning-based 3D segmentation methods struggle with the lack of high-quality training datasets in practical applications. This paper introduces a self-supervised clustering-based network for label-free 3D mesh segmentation, demonstrating its effectiveness through ablation studies and comparative experiments on a standard benchmark.
COMPUTER-AIDED DESIGN
(2023)
Article
Computer Science, Software Engineering
Yi-Ling Qiao, Lin Gao, Jie Yang, Paul L. Rosin, Yu-Kun Lai, Xilin Chen
Summary: This article introduces a deep learning approach to process 3D meshes, which utilizes Laplacian spectral analysis to encode mesh connectivity and employs mesh feature aggregation blocks to gather local and global information. The method outperforms state-of-the-art algorithms in shape segmentation and classification tasks on ShapeNet and COSEG datasets.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Computer Science, Software Engineering
Lin Gao, Tong Wu, Yu-Jie Yuan, Ming-Xian Lin, Yu-Kun Lai, Hao Zhang
Summary: TM-NET is a novel deep generative model that synthesizes textured meshes in a part-aware manner. The model achieves texture compatibility between parts in the same shape through conditional generation and generates high-frequency texture details in a high-dimensional latent space.
ACM TRANSACTIONS ON GRAPHICS
(2021)
Article
Computer Science, Artificial Intelligence
Giuseppe Vecchio, Luca Prezzavento, Carmelo Pino, Francesco Rundo, Simone Palazzo, Concetto Spampinato
Summary: Polygonal meshes are widely used for approximating 3D shapes due to their efficiency and flexibility, but their non-uniformity poses challenges for tasks like segmentation. In this study, a transformer-based method is proposed for semantic segmentation of 3D mesh, aiming to better model the mesh structure using global attention mechanisms. To address the limitations of standard transformer architectures, positional encoding and clustering-based features are introduced. Experimental results demonstrate that the proposed approach achieves state-of-the-art performance on semantic segmentation of 3D meshes.
COMPUTER VISION AND IMAGE UNDERSTANDING
(2023)
Article
Computer Science, Software Engineering
Xi Zou, Sui Bun Lo, Ruben Sevilla, Oubay Hassan, Kenneth Morgan
Summary: This work presents a new method for generating triangular surface meshes in three dimensions for the NURBS-enhanced finite element method. The method allows for triangular elements that span across multiple NURBS surfaces, while maintaining the exact representation of the CAD geometry. This eliminates the need for de-featuring complex watertight CAD models and ensures compliance with user-specified spacing function requirements.
COMPUTER-AIDED DESIGN
(2024)
Article
Biology
Alberto E. Minetti, Luca Ruggiero
Summary: In the past, inertial parameters of body segments were obtained through cadavers, medical 3D imaging, 3D scanning, or geometric approximations, limiting the data to a few species. This study presents a method using commercial 3D meshes of human and animal bodies that can be adjusted and posed according to an underlying skeletal structure for better accuracy. The proposed procedure expands the possibilities of biomechanics research, especially when body size and shape change or external tools are involved.
Article
Computer Science, Interdisciplinary Applications
D. C. Barnes
Summary: A new class of shape functions constructed using continuously-differentiable interpolation methods improves the accuracy and stability of particle motion in electrostatic Particle-In-Cell simulations on simplex meshes.
JOURNAL OF COMPUTATIONAL PHYSICS
(2021)
Article
Chemistry, Multidisciplinary
Hanna Sopha, Adelia Kashimbetova, Michal Baudys, Pavan Kumar Chennam, Marcela Sepulveda, Jakub Rusek, Eva Kolibalova, Ladislav Celko, Edgar B. Montufar, Josef Krysa, Jan M. Macak
Summary: In this study, 3D Ti-Nb meshes with different compositions were produced using direct inkwriting for the first time. The composition of the meshes could be controlled by blending pure Ti and Nb powders. The 3D meshes showed high compressive strength and had potential use in photocatalytic flow-through systems. The Nb-doped TiO2 nanotube (TNT) layers formed on the 3D meshes through wireless anodization showed superior photocatalytic performance for degrading acetaldehyde in a flow-through reactor.
Article
Fisheries
Zita Bak-Jensen, Bent Herrmann, Juan Santos, Valentina Melli, Daniel Stepputtis, Jordan P. Feekings
Summary: Trawl codends are commonly made of diamond-mesh netting, but the variability in mesh geometry compromises the rationality of size selection. Turning the codend netting 45 degrees to achieve better size selection has shown limited evidence. Our study aimed at quantifying the variability in size selection in square-mesh codends and found that standard square-mesh codends had significantly larger variability compared to fixed diamond-mesh codends.
FISHERIES RESEARCH
(2023)
Article
Mathematics, Interdisciplinary Applications
A. Gansen, M. El Hachemi, S. Belouettar, O. Hassan, K. Morgan
Summary: The standard Yee FDTD algorithm is extended to 3D unstructured co-volume meshes using Delaunay primal mesh and high quality Voronoi dual to avoid accuracy losses. This approach has been successfully applied to modeling problems involving various material types and extended to challenging chiral material modeling.
COMPUTATIONAL MECHANICS
(2021)
Article
Computer Science, Information Systems
L. Orazi, B. Reggiani
Summary: This paper presents a novel algorithm for the continuous projection of point triangles belonging to a triangle mesh. The algorithm utilizes the normals defined at the vertices of the triangle for projection and allows the projection direction to vary continuously on the mesh. Additionally, an optimized version of the algorithm is introduced to reduce calculation time. This algorithm can be effectively used for projecting a large set of points onto a coarse mesh.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Runwei Guan, Shanliang Yao, Lulu Liu, Xiaohui Zhu, Ka Lok Man, Yong Yue, Jeremy Smith, Eng Gee, Yutao Yue
Summary: With the development of Unmanned Surface Vehicles (USVs), the perception of inland waterways has become significant. Traditional RGB cameras cannot work effectively in adverse weather and at night, which has led to the emergence of 4D millimeter-wave radar as a new perception sensor. However, the radar suffers from water-surface clutter and irregular shape of point cloud. To address these issues, this paper proposes a high-performance panoptic perception model called Mask-VRDet, which fuses features of vision and radar using graph neural network.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Adrien Le Reun, Kevin Subrin, Anthony Dubois, Sebastien Garnier
Summary: This study aims to evaluate the quality and health of aerospace parts using a high-dimensional robotic cell. By utilizing X-ray Computed Tomography devices, the interior of the parts can be reconstructed and anomalies can be detected. A methodology is proposed to assess both the raw process capability and the improved process capability, with three strategies developed to improve the robot behavior model and calibration.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Weiming Ba, Jung-Che Chang, Jing Liu, Xi Wang, Xin Dong, Dragos Axinte
Summary: This paper proposes a hybrid scheme for kinematic control of continuum robots, which avoids errors through tension supervision and accurate piecewise linear approximation. The effectiveness of the controller is verified on different continuum robotic systems.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Gabriele Abbate, Alessandro Giusti, Viktor Schmuck, Oya Celiktutan, Antonio Paolillo
Summary: In this study, a learning-based approach is proposed to predict the probability of human users interacting with a robot before the interaction begins. By considering the pose and motion of the user, the approach labels the robot's encounters with humans in a self-supervised manner. The method is validated and deployed in various scenarios, achieving high accuracy in predicting user intentions to interact with the robot.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Tiago Cortinhal, Eren Erdal Aksoy
Summary: This work presents a new depth-and semantics-aware conditional generative model, named TITAN-Next, for cross-domain image-to-image translation between LiDAR and camera sensors. The model is able to translate raw LiDAR point clouds to RGB-D camera images by solely relying on semantic scene segments, and it has practical applications in fields like autonomous vehicles.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Marios Krestenitis, Emmanuel K. Raptis, Athanasios Ch. Kapoutsis, Konstantinos Ioannidis, Elias B. Kosmatopoulos, Stefanos Vrochidis
Summary: This paper addresses the issue of informative path planning for a UAV used in precision agriculture. By using a non-uniform scanning approach, the time spent in areas with minimal value is reduced, while maintaining high precision in information-dense regions. A novel active sensing and deep learning-based coverage path planning approach is proposed, which adjusts the UAV's speed based on the quantity and confidence level of identified plant classes.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shota Kokubu, Pablo E. Tortos Vinocour, Wenwei Yu
Summary: In this study, a new modular soft actuator was proposed to improve the support performance of soft rehabilitation gloves (SRGs). Objective evaluations and clinical tests were conducted to demonstrate the effectiveness and functionality of the proposed actuator and SRG.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Jinliang Zhu, Yuanxi Sun, Jie Xiong, Yiyang Liu, Jia Zheng, Long Bai
Summary: This paper proposes an active prosthetic knee joint with a variable stiffness parallel elastic actuation mechanism. Numerical verifications and practical experiments demonstrate that the mechanism can reduce torque and power, thus reducing energy consumption and improving the endurance of the prosthetic knee joint.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Yong You, Jingtao Wu, Yunlong Meng, Dongye Sun, Datong Qin
Summary: A new power-cycling variable transmission (PCVT) is proposed and applied to construction vehicles to improve transmission efficiency. A shift correction strategy is developed based on identifying the changes in construction vehicles' mass and gradient. Simulation results show that the proposed method can correct shift points, improve operation efficiency, and ensure a safer operation process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Shaorui Liu, Wei Tian, Jianxin Shen, Bo Li, Pengcheng Li
Summary: This paper proposes a two-objective optimization technique for multi-robot systems, addressing the issue of balancing productivity and machining performance in high-quality machining tasks.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pengchao Ding, Faben Zhu, Hongbiao Zhu, Gongcheng Wang, Hua Bai, Han Wang, Dongmei Wu, Zhijiang Du, Weidong Wang
Summary: We propose an autonomous approaching scheme for mobile robot traversing obstacle stairwells, which overcomes the restricted field of vision caused by obstacles. The scheme includes stair localization, structural parameter estimation, and optimization of the approaching process.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Pedro Azevedo, Vitor Santos
Summary: Accurate detection and tracking of vulnerable road users and traffic objects are vital tasks for autonomous driving and driving assistance systems. This paper proposes a solution for object detection and tracking in an autonomous driving scenario, comparing different object detectors and exploring the deployment on edge devices. The effectiveness of DeepStream technology and different object trackers is assessed using the KITTI tracking dataset.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
Article
Automation & Control Systems
Benjamin Beiter, Divya Srinivasan, Alexander Leonessa
Summary: Powered exoskeletons can significantly reduce physical workload and have great potential impact on future labor practices. To truly assist users in achieving task goals, a shared autonomy control framework is proposed to separate the control objectives of the human and exoskeleton. Positive Power control is introduced for the human-based controller, while 'acceptance' is used as a measure of matching the exoskeleton's control objective to the human's. Both control objectives are implemented in an optimization-based Whole-Body-Control structure. The results verify the effectiveness of the control framework and its potential for improving cooperative control for powered exoskeletons.
ROBOTICS AND AUTONOMOUS SYSTEMS
(2024)
