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CAREER: Towards General-Purpose Manipulation of Deformable Objects through Control and Motion Planning with Distance Constraints

职业：通过距离约束的控制和运动规划实现可变形物体的通用操纵

基本信息

批准号：
1750489
负责人：
Dmitry Berenson
金额：
$ 54万
依托单位：
Regents of the University of Michigan - Ann Arbor
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1750489&HistoricalAwards=false
关键词：
CAREER Towards General Purpose Manipulation

项目摘要

This project seeks to advance the capabilities of autonomous robots in environments such as factories, hospitals, and homes. To be effective in such settings, robots need to manipulate many kinds of deformable objects, such as cloth, string or wires, and plant or animal tissue. Giving robots the ability to manipulate such objects has the potential to revolutionize the use of robots in several application domains: In manufacturing, allowing robots to pack boxes and handle food and fabric; in medicine, allowing robots to perform tedious tasks in surgery and make hospital beds; and in service, allowing robots to handle clothes and prepare food. However, such tasks are beyond the current state-of-the-art, largely because deformable objects are difficult to model and control. This project will develop new theory, validated with extensive experimentation, that aims to model deformable objects in ways that are amenable to both planning and control. This project will also use manipulation of deformable objects as a motivating problem for students studying robotics at the undergraduate and graduate levels, and in K-12 outreach.This project investigates the fundamentals of modeling, control, and motion planning for deformable objects. This problem is challenging because deformable objects have large state spaces, are extremely-underactuated, and motion planning for these objects requires numerical simulation, which can be computationally expensive and inaccurate. The main hypothesis of this project is that these challenges can be overcome by representing the object and task in terms of distance constraints, which represent allowable distances between parts of the deformable object as well as between the object and parts of the environment, and formulating control and planning methods based on this representation. The expected outcome of this research is an enhanced ability of robots to perform useful tasks, based on a better understanding of deformable object manipulation and a set of broadly-applicable experimentally-verified controllers, planning building-blocks, and planning algorithms.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.

该项目旨在提高自动机器人在工厂、医院和家庭等环境中的能力。为了在这样的环境中发挥作用，机器人需要操纵许多种类的可变形物体，如布、线或电线，以及植物或动物组织。赋予机器人操纵这些物体的能力有可能在几个应用领域彻底改变机器人的使用：在制造业中，允许机器人包装盒子并处理食物和织物;在医学中，允许机器人在手术中执行繁琐的任务并制作病床;以及在服务中，允许机器人处理衣服和准备食物。然而，这样的任务是超出了目前的最先进的，主要是因为可变形的对象是难以建模和控制。该项目将开发新的理论，通过广泛的实验进行验证，旨在以符合规划和控制的方式对可变形物体进行建模。本项目还将使用可变形物体的操纵作为本科生和研究生阶段以及K-12扩展学习机器人的学生的激励问题。本项目研究可变形物体的建模，控制和运动规划的基础。这个问题是具有挑战性的，因为可变形对象具有大的状态空间，是非常欠驱动的，这些对象的运动规划需要数值模拟，这可能是计算昂贵和不准确的。该项目的主要假设是，这些挑战可以通过表示对象和任务的距离约束来克服，这些约束表示可变形对象的各部分之间以及对象和环境的各部分之间的允许距离，并基于此表示制定控制和规划方法。这项研究的预期成果是增强机器人执行有用任务的能力，基于对可变形物体操纵的更好理解和一套广泛适用的实验验证控制器，规划构建块和规划算法。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。