Sensors

Due to the rapid mobility and superior obstacle surmounting capabilities, quadruped robots are increasingly employed in industrial inspections. Quadruped robots usually utilize laser simultaneous localization and mapping (SLAM) for autonomous navigation. However, SLAM is susceptible to inaccuracies under the rapid movement and rotation of quadruped robots.

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Response data for ammonia and ethanol gases was collected using the electronic nose system.To meet the need for accurate, real-time, and stable monitoring of ammonia concentration in the breeding environment in livestock and poultry breeding areas, the electronic nose detection system solved the problems of poor real-time performance and low detection accuracy. An active pumping ammonia detection artificial olfactory system based on a bionic chamber is proposed. The sensing unit of the system consists of a bionic chamber and eight sensors.

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87 Views

Recently, a novel method was proposed to estimate the distance between a couple of wireless transceivers and a reflecting obstacle by analyzing the frequency dependence of the RSS. Although the resolution of this method is rather coarse for typical 2.4 GHz systems, a traffic monitoring system based on that novel approach has been successfully evaluated

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This project is used to examine the actual resolution of a cross talk based TDC. In which, the ZYNQ core is used to provide a reference clock after device start-up. In the meantime, the IDELAY instance inside the LOOP MUX can be adjusted at different tap counts to find out the TDC's resolution. Where, the IDELAY tap delay is determined by comparing it with the reference clock. To be more specific, a crystal clock pulse is brought into the TDC loop by the MMCM. 

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418 Views

The data is uploaded according to the requirements of IEEE DataPort. The file is named 'data of robot control experiments.zip', and it contains two folders. The folder named 'Data of Section IV-B' is the experimental data in Section IV-B, and the folder named 'Data of Appendix A' is the experimental data in Appendix A.

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The accurate classification of landfill waste diversion plays a critical role in efficient waste management practices. Traditional approaches, such as visual inspection, weighing and volume measurement, and manual sorting, have been widely used but suffer from subjectivity, scalability, and labour requirements. In contrast, machine learning approaches, particularly Convolutional Neural Networks (CNN), have emerged as powerful deep learning models for waste detection and classification.

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500 Views

We introduce a novel multi-modal dataset comprising point cloud data from a mmWave radar, RGB and depth images from an RGB-D camera, collected from 23 human subjects.

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this is a dataset for Human-Robot Physical Contact Classification. We used the UR10e six-axis robotic arm as the data collection object and the official tool, RTDE, as the data acquisition tool. Regarding the labels of the dataset, we categorize Human-Robot physical contact into three types: no contact, intentional contact, and collision, based on common occurrences in Human-Robot collaborative tasks. The dataset contains 2375 non-repetitive data entries with valid Human-Robot physical contact information, and each entry includes the motion data of the robotic arm within 1 second.

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69 Views

(Under Construction) The IAMCV Dataset was acquired as part of the FWF Austrian Science Fund-funded "Interaction of Autonomous and Manually-Controlled Vehicles" project. It is primarily centered on inter-vehicle interactions and captures a wide range of road scenes in different locations across Germany, including roundabouts, intersections, and highways. These locations were carefully selected to encompass various traffic scenarios, representative of both urban and rural environments.

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200 Views

To evaluate the proposed odometry method based on 360-degree cameras, we build a new dataset using an Insta-360 One X2 device, which provided high-resolution 4K images captured at a rate of 30 frames per second and 500\,Hz IMU measurements from its built-in IMU.Different from previous datasets, we have set the illumination brightness and the camera movements as the condition variable. The sequence can be classified based on changes in illumination speed or camera movement intensity.

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307 Views

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