NRI: Robotic Tool-Use for Cleaning

NRI：用于清洁的机器人工具

• 批准号: 1524544
• 负责人: Maya Cakmak
• 金额: $ 40.01万
• 依托单位: University of Washington
• 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 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1524544&HistoricalAwards=false
• 关键词: NRI; Robotic; Tool; Use; Cleaning

Cleaning is as one of the most desired capabilities for personal robots, according to reported surveys and interviews conducted with potential users. However, successful solutions to robotic cleaning have so far been special-purpose robots designed for particular cleaning tasks, as with the vacuuming or mopping robots. Instead, this project aims to make general-purpose mobile manipulators perform a much wider range of cleaning tasks, including dusting, wiping, scrubbing, sweeping, or mopping, by enabling them to use human tools. Cleaning is a key activity of daily living and an important task in the maintenance of one's quality of life. Many older adults lose their independence when they can no longer carry out cleaning tasks. Similarly, many mobility-impaired individuals rely on others for cleaning. Robots taking on these tasks could therefore positively impact millions of individuals. General-purpose cleaning robots could also have significant economic impact, similar to those of special-purpose ones like the Roomba. Cleanliness is critical in many commercial facilities, such as hotels or department stores, which involve large surfaces that need to be regularly cleaned in specific ways that programmable cleaning robots developed in this project could handle.General-purpose cleaning robots need to be able to use many different cleaning tools, in many different environments, based on many different user preferences. The diversity of possible situations makes it difficult to develop universal controllers or planners for arbitrary cleaning tasks. Furthermore, it is impossible to know the users' preferences in advance. To address these challenges, this project develops a Learning from Demonstration (LfD) technique that allows a robot to learn cleaning actions from human demonstrations. This technique exploits the common structure of cleaning tasks: they all involve moving a cleaning tool relative to a target surface with a certain pattern while applying a certain force on the surface. Although many LfD approaches already exist, none of them allow learning cleaning actions that generalize to arbitrary surfaces with arbitrary cleaning patterns. This project contributes new representations and learning algorithms that enables a mobile manipulator to clean surfaces of arbitrary size, shape, curvature, dirt distribution, and clutter, using different types of cleaning tools. The methods developed in the project are evaluated with real cleaning tasks through systematic experiments and user studies in the lab, as well as, in the real world through an identical robot deployed in a private home.

根据对潜在用户进行的调查和采访，清洁是个人机器人最期望的功能之一。然而，迄今为止，机器人清洁的成功解决方案是为特定的清洁任务而设计的特殊用途机器人，如吸尘机器人或拖地机器人。相反，该项目旨在通过使通用移动机械手能够使用人类工具来执行更广泛的清洁任务，包括除尘、擦拭、擦洗、扫地或拖地。清洁是日常生活的一项重要活动，也是维持生活质量的一项重要任务。当许多老年人不能再做清洁工作时，他们就失去了独立性。同样，许多行动不便的人也要依靠别人来打扫卫生。因此，机器人承担这些任务可能会对数百万人产生积极影响。与Roomba等特殊用途机器人类似，通用清洁机器人也可能产生重大的经济影响。清洁在许多商业设施中至关重要，例如酒店或百货公司，这些设施涉及需要以特定方式定期清洁的大型表面，该项目开发的可编程清洁机器人可以处理这些清洁。通用的清洁机器人需要能够根据许多不同的用户偏好，在许多不同的环境中使用许多不同的清洁工具。可能情况的多样性使得很难为任意的清洁任务开发通用控制器或计划器。此外，提前知道用户的偏好是不可能的。为了应对这些挑战，该项目开发了一种从演示中学习（LfD）技术，该技术允许机器人从人类演示中学习清洁动作。该技术利用了清洁任务的常见结构：它们都涉及到以特定模式相对于目标表面移动清洁工具，同时在表面上施加特定的力。尽管已经存在许多LfD方法，但它们都不允许学习具有任意清洗模式的任意表面的清洗动作。该项目提供了新的表示和学习算法，使移动机械手能够使用不同类型的清洁工具清洁任意尺寸、形状、曲率、污垢分布和杂乱的表面。项目中开发的方法通过实验室的系统实验和用户研究，以及在现实世界中通过部署在私人家中的相同机器人，与真实的清洁任务进行评估。