NRI: Autonomous Synthesis of Haptic Languages

NRI：触觉语言的自主合成

基本信息

批准号：
1426961
负责人：
Todd Murphey
金额：
$ 58.52万
依托单位：
Northwestern University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2014
资助国家：
美国
起止时间：
2014-08-01 至 2019-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1426961&HistoricalAwards=false
关键词：
NRI Autonomous Synthesis Haptic Languages

项目摘要

This project develops algorithms that enable a robot to physically explore its environment using touch and to construct a language that it can use to describe that environment. The steps include exploring an environment while actively seeking information and then detecting potential elements of a language to describe what was touched. A secondary phase involves taking the set of language elements and compressing the language itself so that sensing, storage, and communication are all more efficient and more robust. The work will use a robot equipped with a robotic arm, hand, and fingertip sensors to describe objects and surfaces it encounters, all without any information about the objects provided beforehand. The importance of the work stems from the need for robots to operate in environments where touch is the only reliable sensory source. For instance, underwater applications often have limited visibility and dexterous manipulation can suffer from visual occlusion due to the hand itself. This research will enable robots to be more responsive to touch and more reliable in vision-impoverished environments.A key technical tool used in this work is ergodic control, a computational technique that finds exploration strategies matching desired statistics. Symbol detection involves finding definitions of dynamic sensor evolution that minimize measures of variability. Language minimization depends on computing the entropy of a language, and finding the minimal language that has the same level of expressiveness. These three mathematical and algorithmic components need to be used in parallel during language creation, and they each have to respect physical limitations on the part of the robot (e.g., computational limitations and physical limitations). Software will be shared through the Robot Operating System (ROS) and TREP (physical simulation and optimal control software).

该项目开发了算法，使机器人能够使用触摸物理探索其环境，并构建一种可以用来描述该环境的语言。这些步骤包括在积极寻求信息的同时探索环境，然后检测一种语言的潜在元素来描述所感动的内容。次要阶段涉及采用一组语言元素并压缩语言本身，以使感应，存储和交流都更加有效，更健壮。这项工作将使用配备有机器人手臂，手和指尖传感器的机器人来描述其遇到的物体和表面，所有这些都没有事先提供的对象的任何信息。作品的重要性源于对机器人在触摸是唯一可靠的感官源的环境中运行的需求。例如，水下应用通常具有有限的可见性，而灵巧的操纵可能会因手本身而受到视觉遮挡。这项研究将使机器人能够对触摸的反应更敏感，并且在视觉突破性的环境中更可靠。这项工作中使用的关键技术工具是Ergodic Control，Ergodic Control，一种计算技术，可以找到与所需统计数据相匹配的勘探策略。符号检测涉及查找动态传感器演变的定义，以最大程度地减少可变性度量。语言最小化取决于计算语言的熵，并找到具有相同表现力的最小语言。这三个数学和算法组件需要在语言创建过程中并行使用，并且它们每个人都必须尊重机器人部分的物理限制（例如，计算限制和物理局限性）。软件将通过机器人操作系统（ROS）和TREP（物理模拟和最佳控制软件）共享。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Automatic synthesis of control alphabet policies

DOI：
10.1109/coase.2016.7743422
发表时间：
2016-08
期刊：
2016 IEEE International Conference on Automation Science and Engineering (CASE)
影响因子：
0
作者：
A. Mavrommati;T. Murphey
通讯作者：
A. Mavrommati;T. Murphey

Real-Time Area Coverage and Target Localization Using Receding-Horizon Ergodic Exploration