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机器人建造分析:虚拟现实模拟

Robotic construction analysis: simulation with virtual reality.

作者信息

Pereira da Silva Nuno, Eloy Sara, Resende Ricardo

机构信息

Instituto Universitário de Lisboa (ISCTE-IUL), ISTAR, Av. das Forças Armadas, 1649-026 Lisboa, Portugal.

出版信息

Heliyon. 2022 Oct 12;8(10):e11039. doi: 10.1016/j.heliyon.2022.e11039. eCollection 2022 Oct.

Abstract

Advances in robotic construction are evident and increasing every year, bringing present and potential improvements. However, the economic and social impacts are hard to assess and quantify without physical in situ testing, which is expensive and time-consuming. This paper presents a methodology for the simulation of robotic construction technologies, namely drones, using a virtual reality environment. Our hypothesis is that a virtual reality simulation of a robotic construction (H1) has the potential of increasing the precision of predicting the construction duration and cost and (H2) allows for the detection of construction problems. The study begins with a review of the literature on drones, robotic arms, and hybrid automatic construction solutions, as well as virtual reality construction simulations, summarising the robotic technologies currently being used, mainly in academic research, to assemble construction elements. It then proposes a construction simulation methodology applied to three architectonic elements to analyse different approaches and different scenarios for robotic construction simulation methodology. A construction simulation is tested, and the data is analysed and compared with traditional construction methods, focussing on construction time and costs.

摘要

机器人建造技术的进步显而易见,且每年都在不断增加,带来了当前的改进以及潜在的提升。然而,若没有实地现场测试,经济和社会影响就难以评估和量化,而实地现场测试既昂贵又耗时。本文提出了一种使用虚拟现实环境来模拟机器人建造技术(即无人机)的方法。我们的假设是,机器人建造的虚拟现实模拟(H1)有提高预测建造工期和成本精度的潜力,且(H2)能够检测出建造问题。该研究首先回顾了有关无人机、机械臂和混合自动建造解决方案以及虚拟现实建造模拟的文献,总结了目前主要在学术研究中用于组装建筑构件的机器人技术。然后提出了一种应用于三个建筑元素的建造模拟方法,以分析机器人建造模拟方法的不同途径和不同场景。对一个建造模拟进行了测试,并对数据进行分析,并与传统建造方法进行比较,重点关注建造时间和成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed08/9586892/ff5192b73323/gr1.jpg

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