NRI: INT: Collaborative Research: Buoyancy-assisted Collaborative Robots That are Cheap, Safe, and Never Fall Down.

NRI：INT：协作研究：廉价、安全且永不摔倒的浮力辅助协作机器人。

• 批准号: 2024768
• 负责人: Sehoon Ha
• 金额: $ 49.7万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024768&HistoricalAwards=false
• 关键词: NRI; INT; Collaborative; Research; Buoyancy

This National Robotics Initiative project will promote the progress of science, advance the national prosperity, welfare, and security; by developing novel buoyancy-assisted collaborative robots that are cheap, safe, and never fall down. The current state of robotics systems is not ready to be deployable to human daily environments, which are challenging for a robot to navigate, especially for legged robots. While they are naturally well-suited for human environments by design, legged robots are often too expensive to scale up for a multi-agent setup, heavy and dangerous to operate near humans, and hard to guarantee stable locomotion. To this end, the ultimate goal of this research is to build collaborative robots that are cheap, safe, and never fall down by exploiting buoyancy to defy a significant amount of gravity This research has the potential for significant impact in enabling deployed locomotion for safe robotic systems interactively assisting humans in daily environments. It provides a principled way for leveraging large amounts of safe and scalable hardware designs with recent advances in machine learning techniques to develop compact representations that are transferable across different robotic systems and human environments. This will innovate how one can utilize a deployable multi-agent system in disaster relief zones and large outdoor environments. The project team will invite general public participation by publicizing the hardware designs and open-sourcing all the deployed software infrastructure. The grant will also support a competition for middle and high school students using the developed low-cost platforms with the goal to foster students’ interest in science, technology, engineering and math (STEM). Creating a new class of locomotion systems has two major challenges: designing a new hardware that is cheap and safe and developing an algorithm for locomotion and collaboration. In order to address these two challenges, this grant will support development of a novel framework that (1) addresses a fundamentally new family of legged robots, namely buoyancy assisted robots (BARs), which are constantly stood-up and highly light-weight by leveraging the inherent "lifting power" of buoyancy; and (2) empowers BARs with reliable locomotion and collaboration skills using deep reinforcement learning algorithms. To this end, the research team will perform interrelated research thrusts centered around the goal of safe, scalable multi-robot systems: developing multiple BARs with each unique locomotion style, learning primitive motor skills for a single agent, extending individually trained agents to orchestrate in a large-scale multi-agent friendly environment.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.

该国家机器人计划项目将通过开发廉价、安全且永不摔倒的新型浮力辅助协作机器人来促进科学进步，促进国家繁荣、福利和安全。可部署到人类日常环境中，这对于机器人的导航来说是一个挑战，特别是对于腿式机器人来说，虽然它们在设计上自然非常适合人类环境，但腿式机器人通常过于昂贵，无法扩展为多智能体设置。 ，重且危险为此，这项研究的最终目标是通过利用浮力抵抗大量重力来制造廉价、安全且永不摔倒的协作机器人。它对于在日常环境中以交互方式协助人类的安全机器人系统的部署运动具有重大影响，它提供了一种原则性方法，可以利用大量安全且可扩展的硬件设计以及机器学习技术的最新进展来开发可在不同环境中转移的紧凑表示。这将创新如何在救灾区和大型户外环境中使用可部署的多代理系统，该项目团队将通过公开硬件设计和开源所有已部署的软件基础设施来邀请公众参与。该赠款还将支持中学生和高中生使用所开发的低成本平台进行竞赛，目的是培养学生对科学、技术、工程和数学 (STEM) 的兴趣，创建新类别的运动系统有两个主要内容。挑战：设计一种廉价的新硬件为了解决这两个挑战，这笔赠款将支持开发一种新颖的框架，该框架（1）解决了一个全新的腿式机器人家族，即浮力辅助机器人（BAR）。通过利用浮力固有的“升力”，使其能够持续站立且重量轻；(2) 使用深度强化学习算法赋予 BAR 可靠的运动和协作技能。相互关联的研究重点围绕安全、可扩展的多机器人系统的目标：开发具有每种独特运动风格的多个 BAR、学习单个代理的原始运动技能、扩展单独训练的代理以在大规模多代理友好环境中进行编排该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

项目成果

PM-FSM: Policies Modulating Finite State Machine for Robust Quadrupedal Locomotion

PM-FSM：用于鲁棒四足运动的有限状态机策略调制

• DOI: 10.1109/iros47612.2022.9982259
• 发表时间: 2021-09-26
• 期刊: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
• 作者: Ren Liu;Nitish Sontakke;Sehoon Ha
• 通讯作者: Sehoon Ha