CAREER: Control and Fractal-based Stability of Dynamic Vision-Based Aperiodic Legged Locomotion

职业：基于动态视觉的非周期腿式运动的控制和基于分形的稳定性

基本信息

批准号：
1944722
负责人：
Koushil Sreenath
金额：
$ 58.61万
依托单位：
University of California-Berkeley
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：
2020-03-01 至 2025-02-28
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1944722&HistoricalAwards=false
关键词：
CAREER Control Fractal based Stability

项目摘要

The goal of this Faculty Early Career Development (CAREER) grant is to enable legged robots that are as sure-footed and agile on rough terrain as snow leopards, mountain goats, and human parkour experts. The project considers two critical questions towards achieving this goal. The first is how the robot can use cameras to decide where and how to take its next few steps. The second is how to make sure that upsets caused by small stumbles and slips fade away over time, instead of growing bigger and eventually causing a fall. The first question will be partially answered by observing how vision and locomotion are connected in humans, and translating that relationship to legged robots. The second question requires extending current mathematical ideas about running and walking. For example, a legged robot might run along a dry path, walk slowly to cross a muddy patch, and then carefully hop on stepping-stones to cross a stream. Current approaches pretend that each basic step is repeated forever. In contrast, this project allows different basic patterns of steps to be combined in any order. Without the ability to navigate realistic terrain and respond to unplanned obstacles, legged robots will be restricted to highly controlled settings. This project will help bring these robots into real-world usage, for tasks involving exploration and security, moving in factories and warehouses, and assisting humans in everyday tasks. The education portion of this project will teach expert skills in dynamics and control through competitive student activities under creativity-enhancing constraints.This project will create control techniques for highly dynamic robots that can run rapidly on extreme terrain, and transition between walking, running, vaulting, jumping, and landing on discrete footholds. These movements require rapid switching between dynamical behaviors based on perceived information of the world. An extension of current theory is needed to analyze the resulting aperiodic locomotion. This project invokes fractal-based theory to define and prove formal stability guarantees. The project also unites deep learning and formal control theory to model and emulate human visual-motor integration for translation to legged robots.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.

该学院早期职业发展（CAREER）资助的目标是使有腿机器人能够像雪豹、山羊和人类跑酷专家一样在崎岖的地形上脚步稳健且敏捷。该项目考虑了实现这一目标的两个关键问题。首先是机器人如何使用摄像头来决定在哪里以及如何采取接下来的几步。第二个问题是如何确保小绊倒和滑倒造成的困扰随着时间的推移而逐渐消失，而不是变得更大并最终导致跌倒。第一个问题将通过观察人类视觉和运动如何连接并将这种关系转化为有腿机器人来部分回答。第二个问题需要扩展当前关于跑步和步行的数学思想。例如，有腿机器人可能会沿着干燥的道路奔跑，慢慢地行走穿过泥泞的土地，然后小心地跳上踏脚石穿过溪流。目前的方法假设每个基本步骤都会永远重复。相比之下，该项目允许以任何顺序组合不同的基本步骤模式。如果无法导航现实地形并响应计划外的障碍物，腿式机器人将被限制在高度受控的环境中。该项目将有助于将这些机器人投入现实世界，用于涉及探索和安全、在工厂和仓库中移动以及协助人类完成日常任务的任务。该项目的教育部分将通过在增强创造力的约束下开展竞争性学生活动，教授动态和控制方面的专业技能。该项目将为高动态机器人创建控制技术，这些机器人可以在极端地形上快速运行，并在步行、跑步、跳马之间转换、跳跃并落在离散的立足点上。这些运动需要根据感知到的世界信息在动态行为之间快速切换。需要对当前理论进行扩展来分析由此产生的非周期性运动。该项目引用基于分形的理论来定义和证明形式稳定性保证。该项目还结合了深度学习和形式控制理论来建模和模拟人类视觉运动整合，以翻译为有腿机器人。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

期刊论文数量（19）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Online Learning of Unknown Dynamics for Model-Based Controllers in Legged Locomotion

DOI：
10.1109/lra.2021.3108510
发表时间：
2021-10
期刊：
IEEE Robotics and Automation Letters
影响因子：
5.2
作者：
Yu Sun;Wyatt Ubellacker;Wen-Loong Ma;Xiang Zhang;Changhao Wang;Noel Csomay-Shanklin;M. Tomizuka;K. Sreenath;A. Ames
通讯作者：
Yu Sun;Wyatt Ubellacker;Wen-Loong Ma;Xiang Zhang;Changhao Wang;Noel Csomay-Shanklin;M. Tomizuka;K. Sreenath;A. Ames

L 1 Adaptive Control Barrier Functions for Nonlinear Underactuated Systems

非线性欠驱动系统的 L 1 自适应控制势垒函数

DOI：
10.23919/acc53348.2022.9867596
发表时间：
2022
期刊：
American Control Conference
影响因子：
0
作者：
Nguyen, Quan;Sreenath, Koushil
通讯作者：
Sreenath, Koushil

Dynamic Legged Manipulation of a Ball by Mini Cheetah Through Multi-Contact Optimization

迷你猎豹通过多接触优化动态腿部操纵球

DOI：
发表时间：
2020
期刊：
Proceedings of the IEEERSJ International Conference on Intelligent Robots and Systems
影响因子：
0
作者：
Yang, Chenyu;Zhang, Bike;Zeng, Jun;Agrawal, Ayush;Sreenath, Koushil
通讯作者：
Sreenath, Koushil

Motion Planning and Feedback Control for Bipedal Robots Riding a Snakeboard

骑蛇板的双足机器人的运动规划和反馈控制

DOI：
10.1109/icra48506.2021.9560963
发表时间：
2021
期刊：
IEEE International Conference on Robotics and Automation (ICRA
影响因子：
0
作者：
Anglingdarma, Jonathan;Agrawal, Ayush;Morey, Joshua;Sreenath, Koushil
通讯作者：
Sreenath, Koushil

Adapting Rapid Motor Adaptation for Bipedal Robots

DOI：
10.1109/iros47612.2022.9981091
发表时间：
2022-01-01
期刊：
2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
影响因子：
0
作者：
Kumar, Ashish;Li, Zhongyu;Malik, Jitendra
通讯作者：
Malik, Jitendra