NRI: INT: Agile and Dynamic Interactions for Mobile Manipulation

NRI：INT：移动操纵的敏捷和动态交互

• 批准号: 1925130
• 负责人: Oliver Kroemer
• 金额: $ 149.89万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1925130&HistoricalAwards=false
• 关键词: NRI; INT; Agile; Dynamic; Interactions

This grant supports research into developing robots that can safely and efficiently work alongside people in crowded spaces, such as warehouses, homes, hospitals, and stores. The goal of the project is to improve quality of life, especially for the elderly, and advance national prosperity. Working in crowded spaces means that the robot comes into direct physical contact with humans and objects, such as doors, shelves, and wheelchairs. Safety is therefore of paramount importance, and the robot needs to give way to humans while also helping them. The robot's interactions with people and objects are often dynamic in nature. For example, a robot may need to physically support a stumbling person while guiding them by the hand, or it may need to use the weight of its own body to open a heavy door. Dynamic interactions like these are beyond the current capabilities of robots. The project uses a new type of robot that balances on a single ball while being able to safely interact with people. The award performs fundamental research into dynamic interactions, by humans and robots, for accomplishing challenging tasks in an efficient, robust, and safe manner. The project provides a deeper understanding of how humans interact with their surroundings, which can also be used in the future for improving ergonomic designs and prosthetic arms. The research team is also developing new algorithms, designs, and controllers for collaborative and assistive robots, which have the potential for widespread societal benefits. Robots capable of safe dynamic interactions, with continuous adaptation and fast reactions, represents a paradigm shift from current approaches. The research provides an end-to-end study of full-body dynamic interaction tasks. The research contributes a series of human subject studies that will provide knowledge of human dynamic interactions. It also develops new dynamic interaction models and novel methods for planning, machine learning, and real-time control of dynamic interactions. To make this research possible, the research team will be utilizing a unique dynamically stable and agile mobile manipulator: the Carnegie Mellon University ballbot. The person-size ballbot locomotes on a single ball wheel, providing omnidirectional motion with intrinsic compliance, and is equipped with two human-scale 7-degree-of-freedom arms with hands. Research contributions to dynamic interaction, planning, learning, and control are demonstrated on this robot platform and rigorously evaluated through a diverse set of integrative tasks, including cooperative carrying, maneuvering a manual wheelchair, cooperative task teaching, sit-to-stand maneuvers, and dynamic navigation in cluttered spaces.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.

这项拨款支持开发机器人的研究，这些机器人可以安全有效地在拥挤的空间中与人一起工作，如仓库，家庭，医院和商店。该项目的目标是提高生活质量，特别是老年人的生活质量，促进国家繁荣。在拥挤的空间中工作意味着机器人与人和物体（如门、货架和轮椅）直接接触。因此，安全至关重要，机器人需要在帮助人类的同时为人类让路。机器人与人和物体的交互通常是动态的。例如，机器人可能需要在用手引导的同时用身体支撑一个绊倒的人，或者它可能需要使用自己身体的重量来打开一扇沉重的门。像这样的动态交互超出了机器人目前的能力。该项目使用了一种新型机器人，它可以在一个球上保持平衡，同时能够安全地与人互动。该奖项对人类和机器人的动态交互进行基础研究，以高效，稳健和安全的方式完成具有挑战性的任务。该项目提供了对人类如何与周围环境互动的更深入的了解，这也可以在未来用于改进人体工程学设计和假肢。该研究团队还在为协作和辅助机器人开发新的算法、设计和控制器，这些机器人有可能带来广泛的社会效益。能够安全动态交互的机器人，具有持续适应和快速反应，代表了当前方法的范式转变。该研究提供了一个端到端的研究全身动态交互任务。这项研究有助于一系列人类主题研究，将提供人类动态互动的知识。它还开发了新的动态交互模型和用于规划，机器学习和动态交互实时控制的新方法。为了使这项研究成为可能，研究小组将利用一种独特的动态稳定和敏捷的移动的机械手：卡内基梅隆大学的球形机器人。人大小的球形机器人在一个球轮上运动，提供具有内在顺应性的全向运动，并配备了两个人类规模的7度自由度手臂。 动态交互，规划，学习和控制的研究贡献在这个机器人平台上得到了展示，并通过一组不同的综合任务进行了严格的评估，包括合作携带，操纵手动轮椅，合作任务教学，坐到站的动作，该奖项反映了NSF的法定使命，并已被认为是值得通过评估使用的支持，基金会的学术价值和更广泛的影响审查标准。

项目成果

Multi-Resolution Sensing for Real-Time Control with Vision-Language Models

使用视觉语言模型进行实时控制的多分辨率传感

• 发表时间: 2023
• 期刊: Proceedings of Machine Learning Research
• 作者: Sharma, Mohit;Saxena, Saumya;Kroemer, Oliver
• 通讯作者: Kroemer, Oliver

SCALE: Causal Learning and Discovery of Robot Manipulation Skills using Simulation

• 发表时间: 2023
• 作者: T. Lee;Shivam Vats;Siddharth Girdhar;Oliver Kroemer

Contact Edit: Artist Tools for Intuitive Modeling of Hand-Object Interactions

联系编辑：用于手部-物体交互直观建模的艺术家工具

• DOI: 10.1145/3592117
• 发表时间: 2023
• 期刊: ACM Transactions on Graphics
• 影响因子: 6.2
• 作者: Lakshmipathy, Arjun Sriram;Feng, Nicole;Lee, Yu Xi;Mahler, Moshe;Pollard, Nancy
• 通讯作者: Pollard, Nancy

Learning Reactive and Predictive Differentiable Controllers for Switching Linear Dynamical Models

学习用于切换线性动态模型的反应性和预测性微分控制器

• 发表时间: 2021
• 期刊: IEEE International Conference on Robotics and Automation
• 作者: Saxena, S.;LaGrassa, A.;Kroemer, O.
• 通讯作者: Kroemer, O.

Contact Tracing: A Low Cost Reconstruction Framework for Surface Contact Interpolation

接触追踪：表面接触插值的低成本重建框架

• 发表时间: 2021
• 期刊: Proceedings of the IEEERSJ International Conference on Intelligent Robots and Systems
• 作者: Lakshmipathy, A.;Bauer, D.;Pollard, N.
• 通讯作者: Pollard, N.