CAREER: A Hybrid Filtering and Robust Control Framework for Legged Robot Locomotion on Dynamic Rigid Surfaces

职业生涯：用于动态刚性表面上的腿式机器人运动的混合过滤和鲁棒控制框架

• 批准号: 2046562
• 负责人: Yan Gu
• 金额: $ 56.47万
• 依托单位: University of Massachusetts Lowell
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2046562&HistoricalAwards=false
• 关键词: CAREER; Hybrid; Filtering; Robust; Control

This Faculty Early Career Development (CAREER) project will focus on creating new methods to model, estimate, and control the movement of legged robots for enabling stable locomotion on dynamic rigid surfaces (DRS) (i.e., surfaces that move and do not deform). While today’s legged robot systems have demonstrated remarkable capabilities in traversing stationary surfaces (e.g., stairs, sand, and grass), legged locomotion on DRS (e.g., ships, aircraft, and trains) is a new robot functionality that has not been addressed. This new functionality will empower legged robots to negotiate complex, dynamic human environments (that are prohibitively challenging for wheeled or tracked robots) to allow them to aid in numerous critical high-risk applications, such as shipboard firefighting and fire suppression and cleaning/disinfection of public transportation vehicles to contain the spread of infectious diseases. Enabling such functionality demands reliable robot estimation and control, which are substantially challenging due to the high complexity of the associated robot behaviors that are hybrid (involving continuous leg-swinging motions and discrete foot-landing events) and subject to the time-varying DRS movement. The CAREER research program seeks to solve these fundamental problems and lay a foundation for the development of next-generation legged robot systems capable of autonomous navigation on nonstationary surfaces. The CAREER education program will enhance the robotics curriculum at the University of Massachusetts Lowell while engaging diverse groups, including underrepresented undergraduate and graduate students, K-12 students, and the general public, in robotics education and research.The research goal of the project is to draw upon dynamic modeling, state estimation, feedback control, and theory of hybrid systems to advance the control theory of legged robots in order to realize provably stable legged locomotion on a DRS. To achieve the research goal, four main objectives will be pursued: (i) formulation of a physics-based model that captures the hybrid, time-varying robot dynamics associated with legged locomotion on a DRS; (ii) creation of new methods of designing state estimators that achieve real-time state estimation with convergence guarantees by provably expanding an invariant filtering methodology from continuous systems to hybrid dynamical systems that include legged robots moving on a DRS; (iii) derivation of a Lyapunov-based controller design methodology to produce stable locomotion on a DRS by handling the hybrid, time-varying robot dynamics under uncertainties that reside in both continuous phases and discrete events; and (iv) integration of the modeling, state estimation, and controller design into a model-based framework that provably sustains legged locomotion on a DRS. The project will support the PI to solve major robotics challenges beyond the capabilities of the state of the art, and help establish a long-term career in robotics and control.This project is supported by the cross-directorate Foundational Research in Robotics program, jointly managed and funded by the Directorates for Engineering (ENG) and Computer and Information Science and Engineering (CISE).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.

这个学院早期职业发展(CAREAGE)项目将专注于创造新的方法来模拟、估计和控制腿部机器人的运动，以实现在动态刚性表面(DRS)(即移动且不变形的表面)上的稳定运动。虽然今天的腿式机器人系统在穿越静止的表面(例如楼梯、沙子和草地)方面表现出了非凡的能力，但在DRS(例如轮船、飞机和火车)上的腿式移动是一种尚未解决的新的机器人功能。这一新功能将使腿式机器人能够适应复杂、动态的人类环境(对于轮式或履带式机器人来说，这是令人望而却步的挑战)，使它们能够协助许多关键的高风险应用，如船上消防和灭火以及公共交通车辆的清洁/消毒，以遏制传染病的传播。实现这种功能需要可靠的机器人估计和控制，由于相关机器人行为的高度复杂性(包括连续的腿部摆动运动和离散的脚着陆事件)并受制于时变的DRS运动，因此这一点具有很大的挑战性。该职业研究计划旨在解决这些根本问题，并为开发能够在非静止表面上自主导航的下一代腿部机器人系统奠定基础。该职业教育计划将加强马萨诸塞大学洛厄尔分校的机器人课程，同时让不同的群体参与机器人教育和研究，包括未被充分代表的本科生和研究生、K-12学生和普通公众。该项目的研究目标是利用动态建模、状态估计、反馈控制和混合系统理论来推进腿式机器人的控制理论，以便在DRS上实现可证明的稳定的腿部运动。为了实现研究目标，将追求四个主要目标：(I)建立基于物理的模型，该模型捕捉与DRS上的腿部运动相关的混合时变机器人动力学；(Ii)创建新的状态估计器设计方法，通过可证明地将不变滤波方法从连续系统扩展到包括在DRS上运动的腿部机器人在内的混合动态系统，实现具有收敛保证的实时状态估计；(Iii)推导基于Lyapunov的控制器设计方法，通过处理驻留在连续和离散事件中的不确定性下的混合时变机器人动力学来产生DRS上的稳定运动；以及(Iv)将建模、状态估计和控制器设计集成到基于模型的框架中，该框架被证明支持DRS上的腿部运动。该项目将支持PI解决超出最先进水平能力的主要机器人挑战，并帮助在机器人和控制领域建立长期的职业生涯。该项目由跨部门机器人基础研究计划支持，该计划由工程总监(ENG)和计算机和信息科学与工程(CEISE)共同管理和资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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

Exponential Stabilization of Periodic LIP walking on a Horizontally Moving Surface

水平运动表面上周期性 LIP 行走的指数稳定性

• 发表时间: 2022
• 期刊: Dynamic Walking Conference
• 作者: Gao, Yuan;Paredes, Victor;Hereid, Ayonga;Gu, Yan
• 通讯作者: Gu, Yan

Analytical Approximate Solution to Mathieu's Equation Enables Real-Time Motion Planning for Legged Robot Walking on a Vertically Moving Surface

马蒂厄方程的解析近似解可实现在垂直移动表面上行走的腿式机器人的实时运动规划

• 发表时间: 2022
• 期刊: Dynamic Walking Conference
• 作者: Iqbal, Amir;Veer, Sushant;Gu, Yan
• 通讯作者: Gu, Yan

Time-Varying ALIP Model and Robust Foot-Placement Control for Underactuated Bipedal Robotic Walking on a Swaying Rigid Surface

摇摆刚性表面欠驱动双足机器人行走的时变 ALIP 模型和鲁棒足部放置控制

• DOI: 10.23919/acc55779.2023.10156254
• 发表时间: 2023
• 期刊: Proceedings of the American Control Conference
• 作者: Gao, Yuan;Gong, Yukai;Paredes, Victor;Hereid, Ayonga;Gu, Yan
• 通讯作者: Gu, Yan

Asymptotic Stabilization of Aperiodic Trajectories of a Hybrid-Linear Inverted Pendulum Walking on a Vertically Moving Surface

垂直运动表面上混合线性倒立摆非周期轨迹的渐近稳定

• DOI: 10.23919/acc55779.2023.10156645
• 发表时间: 2023
• 期刊: IEEE
• 作者: Iqbal, Amir;Veer, Sushant;Gu, Yan
• 通讯作者: Gu, Yan

Invariant Extended Kalman Filtering for Human Motion Estimation with Imperfect Sensor Placement

• DOI: 10.23919/acc53348.2022.9867745
• 发表时间: 2022-05
• 期刊: 2022 American Control Conference (ACC)
• 作者: Zenan Zhu;S. M. R. Sorkhabadi;Yan Gu;Wenlong Zhang