FW-HTF-P: Reshaping Construction Work Conventions: Endowing Collaborative Construction Robots with Social Intelligence for Contextually-Appropriate Robot Behaviors

建筑机器人已经显示出潜在的好处，可以缓解生产率停滞、盈利能力低、事故率高、劳动力短缺等长期存在的问题，建筑机器人市场以超过10%的速度持续增长。随着越来越多的现场建筑机器人被引入工地与人类一起工作，新工作场所的一个新的迫切目标是确保人类同事的安全。在建筑工地，建筑工人经常与其他工人和设备接触。为了避免这种动态环境带来的安全风险，工人们建立了一个共同的社会规范，尊重其他工人的工作惯例，每个人都对其他工人的安全负责。然而，目前大多数建筑机器人不理解这些与工作相关的规范，无法执行类似人类的动作或适应动态的人类行为。为了解决这个问题，这个项目发展资助将支持机器人社会智能的发展，以理解和遵守与建筑工作相关的社会规范。需要这样的智能来增强机器人理解人类行为的能力，并适当地适应人类行为，进而获得人类合作伙伴的信任和接受。本研究可以对建筑工作环境中复杂的人机交互和信任动态建立一个基本的理解。本研究的方法和发现可以扩展到建筑行业以外的各个领域的人机协作，以建立安全有效的人机协作工作场所政策，确保提高安全性和生产率。该项目开发资助旨在探索社会适宜的机器人运动计划者，并检查这些行为是否会影响人机信任动态。本项目拟开展的活动包括：1)理解对理解和预测人类状态和意图至关重要的工作环境；2)探索适合社会规范的机器人运动控制器，用于社会导航和协作操作任务；3)通过信任校准和协商分析人类信任。这些活动将促进和加快社会顺应机器人的发展，通过提高对人类工人意图和社会规范的认识，使其自适应和有效地发挥作用。该团队已经组建了一个独特的跨学科研究小组，横跨土木工程、计算机科学和机器人技术，以实现这一融合的研究目标。这个研究团队将汇集不同学科的观点，以支持融合研究，同时为各自的领域做出贡献。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Construction robots have demonstrated potential benefits to alleviate persistent issues such as stagnant productivity, low profitability, high accident rates, and labor scarcity, and the construction robot market continuously grows at a rate of over 10%. As more and more onsite construction robots are expected to be introduced to jobsite to work with humans, a new imperative objective for a new workplace is to assure the safety of human co-workers. At the construction jobsites, construction workers are constantly in contact with other workers and equipment. To avoid safety risks arising from this dynamic environment, workers have established a shared social norm to respect other workers' work conventions, and every individual is responsible for other workers' safety. However, most of the current construction robots do not understand such work-related norms and are incapable of performing human-like actions or adapting to dynamic human behaviors. To address this issue, this project development grant will support the development of robot social intelligence to understand and abide by work-related social norms in the construction work context. Such intelligence is required to enhance robots' capacities to understand human behaviors, adaptively act upon human behaviors properly, and in turn, acquire trust and acceptance from human co-partners. This research can establish a fundamental understanding of the complex human-robot interactions and trust dynamics in the construction work context. The methods and findings resulting from this research can be extended to human-robot collaboration in various fields outside the construction industry to build a safe and effective human-robot collaborative workplace policy that assures improved safety and productivity.This project development grant aims to explore socially-appropriate robot motion planners and examine whether these behaviors can affect the human-robot trust dynamics. The proposed activities for this project include 1) understanding work contexts that are essential for understanding and predicting human state and intent, 2) exploring social norm-appropriate robot motion controllers for social navigation and collaborative manipulation tasks, and 3) analyzing human trust via trust calibration and negotiation. These activities will facilitate and expedite the development of socially compliant robots to function adaptively and efficiently through improved recognition of human workers' intentions and social norms. The team has formed a unique interdisciplinary group of researchers across civil engineering, computer science, and robotics to achieve this convergent research objective. This research team will bring together diverse disciplinary perspectives to support convergence research while contributing to their domains.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.