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Infrastructure less approach for ubiquitous user location tracking in construction environments

机译:在建筑环境中无处不在的用户位置跟踪的少基础设施方法

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摘要

Current research trends in the field of automation in construction focus on automating traditional tasks with the intent of improving the accuracy and streamlining the flow of information throughout the construction process. One viable, potentially automated task is site inspection. This consists of a set of vital yet notoriously laborious, costly, time-consuming, and error-prone activities, when performed manually by site inspectors. Incorporating recent contributions from the fields of inertial-based step detection and vision-based egomotion estimation, this paper develops and evaluates infrastructureless inertial and visual systems to ubiquitously localize people in construction environments. The implementation and the results obtained from validation experiments demonstrate that a lightweight, portable, and cost-effective hybrid inertial-vision tracking system provides the most promise for accurate, precise, and robust localization of mobile users in construction environments. It achieves, on average, an accuracy of around 1% of the total traveled distance, compared to the INS and vision systems that provide an accuracy of less than 2% and 3% of the total traveled distance respectively. (C) 2015 Elsevier B.V. All rights reserved.
机译:当前建筑自动化领域的研究趋势集中在自动化传统任务上,目的是提高整个建筑过程的准确性并简化信息流。一种可行的,可能是自动化的任务是现场检查。当由现场检查人员手动执行时,这包括一组重要但又费力费力,昂贵,耗时且容易出错的活动。结合基于惯性的阶跃检测和基于视觉的自我运动估计领域的最新贡献,本文开发并评估了无基础设施的惯性和视觉系统,以使人们在建筑环境中无处不在。验证实验的实现和结果表明,轻巧,便携式且经济高效的混合惯性视觉跟踪系统为在建筑环境中对移动用户进行准确,精确和可靠的本地化提供了最大的希望。与INS和视觉系统相比,它的平均准确度约为总行驶距离的1%,而INS和视觉系统的准确度分别低于总行驶距离的2%和3%。 (C)2015 Elsevier B.V.保留所有权利。

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