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Multi-person Collaborative Hoisting Training System Based on Mixed Reality

机译:基于混合现实的多人协作吊装训练系统

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摘要

In the early stage of hoisting training, virtual hoisting training equipment is often used to avoid safety accidents caused by lack of experience. However, there are some problems in the existing virtual training equipment, such as single interaction mode, limited viewing angle, and the system that is not portable. To solve the problems, a multi-person cooperative hoisting training system based on mixed reality is proposed in this paper. To ensure the accuracy of the virtual model, on the basis of collecting a large number of actual data, the system employs Pro/E software to carry out 3D accurate modeling of the box hoisting cart. In an effort to ensure the positioning accuracy of the holographic virtual model, the system firstly adopts image recognition method for initial positioning, SLAM algorithm for real-time positioning, and spatial anchor point for accurate positioning. In order to solve the problem of multi-person cooperative training, the system adopts the hardware composition of a server, a plurality of mixed reality intelligent glasses, a wireless router and so on, and uses gesture interaction and wireless analog controller interaction to realize efficient human-machine interaction. Via comparative experiments, it is proved that the system can greatly improve the operation level of operators and is of use value.
机译:在提升训练的早期阶段,虚拟吊装训练设备通常用于避免由于缺乏经验而引起的安全事故。然而,现有的虚拟训练设备存在一些问题,例如单个交互模式,有限的视角和不便携的系统。为了解决问题,本文提出了一种基于混合现实的多人合作吊装训练系统。为了确保虚拟模型的准确性,在收集大量实际数据的基础上,系统采用Pro / E软件进行3D精确建模的盒子吊装车。为了确保全息虚拟模型的定位精度,系统首先采用用于初始定位的图像识别方法,用于实时定位的SLAM算法,以及用于精确定位的空间锚点。为了解决多人合作培训的问题,系统采用服务器的硬件组成,多个混合现实智能眼镜,无线路由器等,并使用手势交互和无线模拟控制器交互来实现高效人机相互作用。通过比较实验,证明该系统可以大大提高操作员的运行水平,并且是使用价值。

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