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NRI: FND: Bioinspired Design and Shared Autonomy for Underwater Robots with Soft Limbs

NRI：FND：软肢水下机器人的仿生设计和共享自主权

基本信息

批准号：
1734627
负责人：
Geoffrey Hollinger
金额：
$ 68.66万
依托单位：
Oregon State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-15 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734627&HistoricalAwards=false
关键词：
NRI FND Bioinspired Design Shared

项目摘要

Currently, delicate and challenging underwater manipulation tasks are performed only by human divers when it is safe for them to enter the environment. Robots can help address this issue by distancing human operators from dangerous environments, while still leveraging their skills in planning complex manipulation tasks. Rigid robotic manipulators, however, are typically not suitable for delicate manipulation tasks. To address this limitation, this project explores the design and control of soft robotic arms inspired by the octopus. Soft robots can perform delicate tasks of scientific interest in underwater environments, such as retrieving biological samples or delicate artifacts, without harming them. Such soft robots can also be safer when operating alongside humans. The results of the research will be integrated into hands-on courses as part of the Oregon State University PhD in Robotics and into K-12 outreach via the OSU Robotics Club and Oregon FIRST Robotics competitions.The objective of this research is to establish a framework for underwater manipulation, combining shared autonomy between human operators and robots with mechanically-directed soft actuation and sensing. The proposed work will examine new actuator morphologies, alternative fabrications techniques, and the use of stretchable integrated liquid metal sensors. To control the soft grippers, this project develops a planning and control interface that utilizes machine learning techniques to leverage human operators' skills at quickly identifying stable grasps. The physical attributes of the soft grippers will be designed in tandem with algorithms, which will provide improved understanding of underwater interaction and shared autonomy. Dexterity and compliance of the soft manipulators will be evaluated for large contact-area, multi-point gripping, which is particularly advantageous for grasping delicate objects underwater. Testing will be done in a benchtop underwater test bed, using kinematic motion capture and interaction forces to evaluate performance.

目前，只有人类潜水员在安全进入环境时才能执行精细和具有挑战性的水下操纵任务。机器人可以帮助解决这个问题，让人类操作员远离危险环境，同时仍然利用他们的技能来规划复杂的操作任务。然而，刚性机器人操纵器通常不适合精细的操纵任务。为了解决这一限制，该项目探索了受章鱼启发的软机器人手臂的设计和控制。软体机器人可以在水下环境中执行科学感兴趣的精细任务，例如取回生物样本或精致的文物，而不会伤害它们。这种软体机器人在与人类一起操作时也更安全。这项研究的结果将被整合到实践课程的一部分，俄勒冈州立大学机器人博士学位，并通过OSU机器人俱乐部和俄勒冈州第一机器人竞赛进入K-12推广。这项研究的目标是建立一个框架，水下操纵，结合人类操作员和机器人之间的共享自主权与机械定向软驱动和传感。拟议的工作将研究新的致动器形态，替代制造技术，以及使用可拉伸集成液态金属传感器。为了控制软夹持器，该项目开发了一个规划和控制界面，利用机器学习技术来利用人类操作员的技能快速识别稳定的抓持。软夹持器的物理属性将与算法一起设计，这将提供对水下互动和共享自主性的更好理解。灵活性和顺应性的软机械手将评估大接触面积，多点夹持，这是特别有利于抓住微妙的物体水下。测试将在台式水下测试台上进行，使用运动学运动捕获和相互作用力来评估性能。