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.

这个教师的早期职业发展（职业）项目将着重于创建新的方法来建模，估计和控制腿部机器人的运动，以在动态刚性表面（DRS）上稳定运动（即移动和不变形）。虽然今天的腿部机器人系统在遍历固定表面（例如电台，沙子和草地）中表现出了显着的功能，但DRS上的腿部机动（例如，船舶，飞机和火车）是一种新的机器人功能，是一种新的机器人功能。这种新功能将使腿部机器人能够协商复杂的，动态的人类环境（被禁止挑战轮式或轨道机器人），以使它们能够帮助他们进行许多关键的高风险应用，例如船上消防，抑制灭火，清洁/消毒，以包含感染性疾病的传播。使此类功能要求可靠的机器人估计和控制，这是由于混合动力的相关机器人行为的高复杂性（涉及连续的腿部旋转动作和离散的步行地面事件），并且受时间变化的DR运动。职业研究计划旨在解决这些基本问题，并为开发下一代腿部机器人系统的发展奠定了基础，能够自主导航在非组织中的职业教育计划将增强马萨诸塞州洛厄尔大学的机器人课程，同时吸引多样性的学生，包括对学生的培训不足的学生，k-12的学生，包括一般的学生，以及一般性的学生，以及一般性的学生，以及一般的公众，并在一般的学生中培训了一般的公众。通过动态建模，状态估计，反馈控制和混合系统理论，以推进腿部机器人的控制理论，以便在DRS上实现适当稳定的腿部运动。为了实现研究目标，将实现四个主要目标：（i）基于物理的模型的公式，该模型捕获了与DRS上与腿部运动相关的混合，随时间变化的机器人动力学； （ii）创建设计新方法的设计状态估计器，以实现实时状态估计，并通过可能将不变的过滤方法从连续系统扩展到混合动态系统，包括在DRS上移动的腿部机器人； （iii）基于lyapunov的控制器设计方法的推导，以在不确定性的不确定性下处理混合型，随时间变化的机器人动力学，从而在DRS上产生稳定的运动，这些机器人动态存在于连续阶段和离散事件中； （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，该框架适当地维护了DRS上的腿部运动。该项目将支持PI解决主要机器人技术的挑战，超出了艺术状态的能力，并帮助建立了机器人和控制的长期职业。该项目得到了机器人计划中的跨导向基础研究的支持，共同管理和资助了由工程局（ENG）和信息科学和工程（CISE）的奖项。使用基金会的智力优点和更广泛的影响评估标准进行评估。

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

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

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