Sensor calibration is the fundamental block for a multi-sensor fusion system. This paper presents an accurate and repeatable LiDAR-IMU method (termed LI-Calib), to calibrate 6-DOF extrinsic transformation between 3D LiDAR Inertial Measurement Unit (IMU). Regarding high data capture rate IMU sensors, LI-Calib adopts continuous-time trajectory formulation based on B-Spline, which more suitable fusing high-rate or asynchronous measurements than discrete-time approaches. Additionally, decomposes...

Accurate and reliable sensor calibration is essential to fuse LiDAR inertial measurements, which are usually available in robotic applications. In this article, we propose a novel LiDAR-IMU method within the continuous-time batch-optimization framework, where intrinsics of both sensors spatial-temporal extrinsics between calibrated without using infrastructure, such as fiducial tags. Compared discrete-time approaches, formulation has natural advantages for fusing high-rate measurements from...

In an unmanned orchard, various tasks such as seeding, irrigation, health monitoring, and harvesting of crops are carried out by vehicles. These vehicles need to be able distinguish which objects fruit trees not, rather than relying on human guidance. To address this need, study proposes efficient robust method for tree detection in orchard point cloud maps. Feature extraction is performed the 3D form a two-dimensional feature vector containing three-dimensional information target detected...

In this paper, we propose a highly accurate continuous-time trajectory estimation framework dedicated to SLAM (Simultaneous Localization and Mapping) applications, which enables fuse high-frequency asynchronous sensor data effectively. We apply the proposed in 3D LiDAR-inertial system for evaluations. The method adopts non-rigid registration simultaneously removing motion distortion LiDAR scans. Additionally, two-state correction efficiently tackle computationally-intractable global...

Accurate reconstruction of plant models for phenotyping analysis is critical optimizing sustainable agricultural practices in precision agriculture. Traditional laboratory‐based phenotyping, while valuable, falls short understanding how plants grow under uncontrolled conditions. Robotic technologies offer a promising avenue large‐scale, direct real‐world environments. This study explores the deployment emerging robotics and digital technology to improve performance efficiency. Three...

ABSTRACT In automated lychee harvesting, the complex geometric structures of branches, leaves, and clustered fruits pose significant challenges for robotic cutting point detection, where even minor positioning errors can lead to harvest damage operational failures. This study introduces Fcaf3d‐lychee network model, specifically designed precise picking localization. The data acquisition system utilizes Microsoft's Azure Kinect DK time‐of‐flight camera capture cloud through multi‐view...

As the Internet of Things (IoT) rapidly proliferate in world, new attacks exploiting weaknesses unfledged IoT technologies are emerging constantly. An Intrusion Detection System (IDS) is a powerful tool to defend systems against security threats by monitoring abnormal activities on networks. an effective approach detecting malicious behaviors, Machine Learning (ML) has gained substantial interest from researchers. ML-based IDS framework for proposed this study and ten learning methods...

This study presents the Fast Fruit 3D Detector (FF3D), a novel framework that contains neural network for fruit detection and an anisotropic Gaussian-based next-best view estimator. The proposed one-stage detector, which utilizes end-to-end network, shows superior accuracy robustness compared to traditional 2D methods. core of FF3D is object based on convolutional (3D CNN) followed by estimation module. innovative architecture combines point cloud feature extraction tasks, achieving accurate...

Functionalities with corrected inter-site distance in porous materials enable them to work a concerted manner.

A porous superacid material with a high surface area and abundant accessible active sites is rationally designed, showing outstanding catalytic activities durability in industrial chemical transformations.

In order to detect different biological features and dynamic tiny targets with subtle more accurately efficiently analyze the differences of features, this paper proposes classifying identifying local contour edge images types reveals high similarities in their features. Taking pigeons as objects, there is little difference appearance between female male pigeons. Traditional methods need manually observe morphology near anus identify sex or carry out chromosome examination even molecular...

Curcumin is exploited as a modifier for ZnO electron-transport layers to simultaneously improve the efficiency and photostability of inverted organic solar cells.

Accurate collection of plant phenotyping is critical to optimising sustainable farming practices in precision agriculture. Traditional controlled laboratory environments, while valuable, falls short understanding growth under real-world conditions. Emerging sensor and digital technologies offer a promising approach for direct plants farm environments. This study investigates learning-based method using the Neural Radiance Field achieve accurate in-situ pepper greenhouse To quantitatively...

With the rapid development of turtle breeding industry in China, demand for automated sorting is increasing. The automatic Chinese softshell turtles mainly consists three parts: visual recognition, weight prediction, and individual sorting. This paper focuses on two aspects, i.e., recognition a novel method object detection prediction proposed. In process, computer vision technology used to estimate classify them by weight. For body parts turtles, color space model proposed this separate...

Polymerase chain reaction (PCR) technology is a method for amplifying specific target DNA sequence in vitro; thermoelectric cooler (TEC) used thermal-cycler system to implement periodic heating and cooling. Finite element models of multi-stage TEC PCR based on were established with ANSYS Workbench 12.0 thermal-electric coupled-field analysis elements. The steady-state thermal performances XLT2389 different driving currents analyzed by this model. simulation results indicated that the...

We present a novel approach for metric dense depth estimation based on the fusion of single-view image and sparse, noisy Radar point cloud. The direct heterogeneous data, or their encodings, tends to yield maps with significant artifacts, blurred boundaries, suboptimal accuracy. To circumvent this issue, we learn augment versatile robust monocular prediction scale induced from sparse data. propose Radar-Camera framework highly accurate fine-detailed four stages, including prediction, global...

Digital modelling stands as a pivotal step in the realm of Twinning. The future trend Twinning involves automated exploration and environmental complex scenes. In our study, we propose an innovative solution for robot odometry, path planning, unknown outdoor environments, with focus on modelling. approach uses minimum cost formulation pseudo-randomly generated objectives, integrating multi-path planning evaluation, emphasis full coverage maps based feasible boundaries interest. allows...

Accurate reconstruction of plant models for phenotyping analysis is critical optimising sustainable agricultural practices in precision agriculture. Traditional laboratory-based phenotyping, while valuable, falls short understanding how plants grow under uncontrolled conditions. Robotic technologies offer a promising avenue large-scale, direct real-world environments. This study explores the deployment emerging robotics and digital technology to improve performance efficiency. Three...

Accurately identifying lychee-picking points in unstructured orchard environments and obtaining their coordinate locations is critical to the success of robots. However, traditional two-dimensional (2D) image-based object detection methods often struggle due complex geometric structures branches, leaves fruits, leading incorrect determination lychee picking points. In this study, we propose a Fcaf3d-lychee network model specifically designed for accurate localisation Point cloud data natural...

Environmental mapping and robot navigation are the basis for realizing automation in modern agricultural production. This study proposes a new autonomous method gardening scene robots. First, LiDAR slam-based semantic algorithm is proposed to enable robots analyze structural information from point cloud images generate roadmaps them. Secondly, general framework shortest global path according road map, consider local terrain find optimal achieve safe efficient trajectory tracking; this...