Single-vehicle light detection and ranging (LiDAR) has limitations in capturing comprehensive environmental information. The advancement of vehicle-to-infrastructure (V2I) collaboration presents a potent solution to this challenge. During the collaboration, point cloud registration precisely aligns data from various LiDARs, effectively mitigating the constraints associated with data collection by a single-vehicle LiDAR. Registration furnishes autonomous vehicles with a more comprehensive and dependable environmental understanding. Currently, there are various types and performances of LiDAR in practical application scenarios. So, it is more necessary to perform heterogeneous point cloud registration, and there is still a relatively large room for improvement. Consequently, we introduce a coarse-to-fine approach to heterogeneous point cloud registration (C2F-HPCR), establishing the inaugural benchmark for point cloud registration in intricate vehicle-infrastructure collaboration contexts. C2F-HPCR acquires an initial registration matrix through its coarse registration module. Subsequently, it uses the overlap estimation module to extract overlap points between two point clouds. These identified points are inputted into the fine registration module to obtain the final registration matrix. Experiments on the DAIR-V2X-C dataset demonstrate that the recall of C2F-HPCR in heterogeneous point cloud registration is 72.99%. C2F-HPCR shows strong performance in heterogeneous point cloud registration, facilitating efficient registration of vehicle-side point clouds and infrastructure-side point clouds. The code is available at https://github.com/916718212/C2F-HPCR
In order to enrich the diversity of interactive recognition methods, an interactive method of gesture recognition based on static vision is proposed. The static gesture images are captured by color camera in real time. The gesture is extracted based on FHOG features. The extracted eigenvalues are used as input of SVM multi-class classifier to recognize gesture actions. The gesture features are used to locate feature points to achieve the segmentation of gesture recognition and gesture recognition. The experimental results show that the system can recognize six common static gestures. The system has good robustness, with an average recognition rate of 95.31%, a rejection recognition rate of 9.37%, and an overall recognition efficiency of 90.63%.
The conventional training for automobile assembly and disassembly has such weak points as need of ample space, lack of teachers, heavy loss of instruments, low efficiency and unsatisfactory training results. This article puts forward a kind of automobile assembly technology based on virtual reality (shortened as VR). With the help of HTC VIVE helmet display and handle as the input and output media, the interactive connection between the user and the virtual scene is established. Lead the structured automobile model into the Unity 3D development engine, and write the script using the object-oriented programming method of C# language, to realize automobile virtual assembly processes, which includes such major functions as main scene design, component recognition, assembly demonstration, virtual assembly and simulated driving. This technology, featuring rich content, short cycle, low cost, flexible and easy use, strong user experience, low risk, lead and play, and strong expansibility, etc., has good practical significance for current automobile assembly.
In the field of Waste LCD disassembling and recycling, there are existing two major problems: 1) disassembling waste LCD mainly depends on manually mechanical crushing; 2) the resource level is not high. In order to deal with the above problems, in this paper, we develop an efficient, safe and automated waste LCD disassembling assembly line technology. This technology can disassembly and classify mainstream LCD into four components, which are liquid crystal display panels, housings and metal shield, PCB assembly. It can also disassembly many kinds of waste LCD. Compared with the traditional cooperation of manual labor and electric tools method, our proposed technology can significantly improve disassembling efficiency and demonstrate good prospects and promotional value.
Removing the screws on the sides of a shield is a necessary process in disassembling a computer LCD display. To solve this issue, a platform has been designed for removing the screws on display shields. This platform uses virtual instrument technology with LabVIEW as the development environment to design the mechanical structure with the technologies of motion control, human-computer interaction and target recognition. This platform removes the screws from the sides of the shield of an LCD display mechanically thus to guarantee follow-up separation and recycle.
This paper designs a thermal battery infrared monitoring system using FLUKE Ti45 Thermal Imagers and IMAQ
Vision software of LabVIEW. The thermal battery infrared monitoring system uses infrared imaging technology to
monitor the electrical property testing process. It can investigate and analyze the working performance of thermal
batteries on different kinds of maximum conditions, and monitor the temperature variation tendency.
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