Smart Crane Director: Smart Technologies to Facilitate Safer and More Efficient Erections

智能起重机总监：智能技术促进更安全、更高效的安装

• 批准号: RGPIN-2019-04659
• 负责人: Kang, ShihChung
• 金额: $ 2.26万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=737767
• 关键词: Smart; Crane; Director; Technologies; Facilitate

Background Cranes are the most crucial equipment in construction sites. Improving crane operations will directly increase the productivity and safety in many construction projects. With 17 years of research on cranes, the applicant proposes a five-year program to extend those technologies to facilitate the crane operations. A Five-Year Plan to Discover Knowledge and Develop a System In the first year, the research team will use machine learning algorithms to enhance the perception of crane operators. They will collect a considerable number of images from the views of crane operators (i.e. bird's-eye views) and manually tag the "critical objects," such as excavators, trucks, and workers, in those images. Using the image dataset, the researchers will employ machine learning algorithms to develop a real-time method to identify such objects to alert operators of risks and to proactively provide real-time guidance for safe, efficient erections. In the second year, the applicant will shift the focus to precise control to minimize cable sway. He and his research team will develop control algorithms that can generate a series of fine motion controls to reduce the sway from inertial forces. The third year, the applicant will focus on erection planning to generate collision-free operation paths. By integrating the knowledge discovered in the first two years, the path planner will not only minimize cable sway but will also avoid passing over personnel. The fourth year, the applicant will build a user interface to link perception, sway control, and path planner in guiding system for crane operations, tentatively coined as Smart Crane Director. In the fifth year, a field test will be conducted to ensure the overall usability of the system. Broader Impacts from the Grant This research brings cutting-edge technologies to the front line of construction sites and will bring three broad impacts to future constructions. 1. Better operations: With the proactive guidance from the system, the erections will be safer and more efficient, and thus will be a more productive and predictable construction process. 2. Better training: This research will benefit training for crane operators. The entire erection process can be logged and analyzed using the algorithms we will develop. These will allow for scoring the operational qualities for each lift and increase the learning of the best practices in a shorter time frame. 3. Toward future construction: This research will be fundamental to teleoperation in the future. With the capacity of perception, crane control, and erection path planning, operators may not need to work inside the job site. Instead, they may work remotely in safety to control the crane with a fully focused mind.

背景起重机是建筑工地中最关键的设备。改善起重机的操作将直接提高许多建筑项目的生产率和安全性。在对起重机进行了17年的研究后，申请人提出了一项为期五年的计划，以扩展这些技术，以促进起重机的操作。发现知识和开发系统的五年计划在第一年，研究团队将使用机器学习算法来增强起重机操作员的感知。他们将从起重机操作员的视角(即鸟瞰)收集相当数量的图像，并手动标记这些图像中的“关键对象”，如挖掘机、卡车和工人。使用图像数据集，研究人员将使用机器学习算法来开发一种实时方法来识别此类对象，以提醒操作员风险，并主动为安全、高效的勃起提供实时指导。在第二年，申请者将把重点转移到精确控制上，以最大限度地减少缆索摇摆。他和他的研究团队将开发控制算法，这些算法可以产生一系列精细的运动控制，以减少惯性力的摇摆。第三年，申请人将重点架设规划，生成无碰撞作业路径。通过整合前两年发现的知识，路径规划者不仅可以最大限度地减少缆绳摇摆，还可以避免忽略人员。第四年，申请者将建立一个用户界面，将起重机操作的导航系统中的感知、摇摆控制和路径规划联系起来，暂定为智能起重机导向器。在第五年，将进行实地测试，以确保该系统的整体可用性。这项研究将尖端技术带到了建筑工地的前线，并将给未来的建筑带来三个广泛的影响。1.更好的操作：在系统的主动指导下，架设将更加安全和高效，因此将是一个更有成效和可预测的施工过程。2.更好的培训：本研究将对起重机操作员的培训有所裨益。整个架设过程可以使用我们将开发的算法进行记录和分析。这将允许对每台电梯的操作质量进行评分，并在较短的时间内增加对最佳做法的学习。3.面向未来的建设：这项研究将是未来遥操作的基础。有了感知、起重机控制和安装路径规划的能力，操作员可能不需要在工作现场内工作。取而代之的是，他们可能会在安全的情况下远程工作，以全神贯注地控制起重机。