NRI: A Proactive Approach to Managing Contingencies during Human Robot Collaboration in Manufacturing

NRI：在制造中人机协作过程中管理意外事件的主动方法

• 批准号: 1527220
• 负责人: Satyandra Gupta
• 金额: $ 63.91万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2016-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1527220&HistoricalAwards=false
• 关键词: NRI; Proactive; Approach; Managing; Contingencies

Recent advances in human-safe industrial robots present an opportunity for creating hybrid work cells, where humans and robots can collaborate in close physical proximities. This capability enables realizing systems that utilize complementary strengths of humans and robots. Several new low-cost robots have been introduced in the market over the last few years, making them attractive in many new manufacturing applications. This makes the idea of hybrid cells economically viable for small and medium manufacturers, which represent a very important segment of the manufacturing sector in the United States. Both humans and robots can make errors in a hybrid cell, hence creating contingency situations. Unless handled promptly, a contingency situation may lead to significant operational inefficiencies. Hence, hybrid cells are not likely to cost-effective unless contingency situations are proactively detected and managed. This National Robotics Initiative (NRI) award supports fundamental research to enable proactive management of contingencies arising during human-robot collaboration in hybrid work cells in small production volume manufacturing operations. Results from this research will enable introduction of industrial robots in small production volume operations and are expected to make US manufacturing industry cost competitive in the global market. The integration of the research with graduate and undergraduate courses will enhance the robotics and manufacturing curricula and enrich learning experiences of the participating students. Outreach activities will educate and inform K-12 students about career opportunities in robotics and manufacturing. Fundamental advances are needed in automated planning, cell monitoring, replanning, and human-robot interaction to endow hybrid cells with effective contingency handling capabilities. This research will investigate computational foundations for the design of task planning and resource allocation algorithms that explicitly account for managing contingencies. Algorithms will be developed for real-time monitoring of the task progress to ensure that tasks are completed in a safe and efficient manner. Real-time replanning algorithms will be designed to handle contingencies and refine plans based on the observed task execution performance. This research will also explore and characterize methods for effective information exchange between humans and robots to deal with contingencies.

人类安全工业机器人的最新进展为创造混合工作单元提供了机会，人类和机器人可以在物理上密切合作。这种能力使系统能够利用人类和机器人的互补优势。在过去的几年里，市场上已经推出了几种新的低成本机器人，使它们在许多新的制造应用中具有吸引力。这使得混合电池的想法对中小型制造商来说在经济上是可行的，这些制造商代表着美国制造业的一个非常重要的部分。人类和机器人都可能在混合细胞中出错，从而产生意外情况。除非迅速处理，否则紧急情况可能会导致严重的业务效率低下。因此，除非主动发现和管理应急情况，否则混合电池不太可能具有成本效益。这一国家机器人倡议(NRI)奖支持基础研究，以实现对小批量制造操作中混合工作单元中的人-机器人协作过程中出现的意外情况进行主动管理。这项研究的结果将使工业机器人能够在小批量操作中引入，并有望使美国制造业在全球市场上具有成本竞争力。将研究与研究生和本科课程相结合，将加强机器人和制造课程，并丰富参与学生的学习经验。外展活动将教育和告知K-12学生在机器人和制造领域的职业机会。需要在自动化规划、细胞监测、重新规划和人机交互方面取得根本性进展，以赋予杂交细胞有效的应急处理能力。这项研究将调查设计任务规划和资源分配算法的计算基础，这些算法明确地说明了管理意外情况的原因。将开发实时监测任务进度的算法，以确保以安全和高效的方式完成任务。将设计实时重新计划算法来处理意外情况，并根据观察到的任务执行性能改进计划。这项研究还将探索和表征人类和机器人之间有效信息交换的方法，以应对突发事件。