RI: Small: Interactive Perception for Manipulating Non-Rigid Objects

RI：小：操纵非刚性物体的交互式感知

• 批准号: 1017007
• 负责人: Ian Walker
• 金额: $ 41.79万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1017007&HistoricalAwards=false
• 关键词: RI; Small; Interactive; Perception; Manipulating

Traditional robotics research has adopted a sense-plan-act paradigm in which it is assumed that the sensors are capable of providing enough information in order to decide the next course of action. Humans and animals, however, frequently adopt a different approach, such as shuffling through a pile of unknown objects in order to identify an item of interest hidden beneath the pile. This project explores the concept of interactive perception (or manipulated-guided sensing), in which successive manipulations of objects in an environment are used to increase vision-based understanding of that environment, and vice versa. In particular, the project involves developing appropriate low-order models of highly non-rigid structures such as fabrics and textiles; constructing algorithms to perform real-time vision-based sensing of such objects in cluttered, unstructured environments; and building prototype robotic hardware for testing the resulting models and algorithms. The research forms an integral part of next-generation household service robots performing everyday tasks such as sorting and folding laundry.

传统的机器人研究采用了一种感知-计划-行动的范式，在这种范式中，假设传感器能够提供足够的信息来决定下一步的行动。然而，人类和动物经常采用不同的方法，比如在一堆未知物体中洗牌，以识别隐藏在这堆物体下面的感兴趣的物体。该项目探索了交互式感知（或操纵引导传感）的概念，其中使用对环境中物体的连续操作来增加对该环境的基于视觉的理解，反之亦然。该项目特别涉及开发高度非刚性结构（如织物和纺织品）的适当低阶模型；构建算法，在混乱、非结构化的环境中对这些物体进行实时的基于视觉的感知；并构建机器人硬件原型，以测试生成的模型和算法。这项研究是下一代家庭服务机器人的组成部分，这些机器人可以完成分类和折叠衣服等日常任务。