Asymmetric Gait Generation for Legged Locomotion in Complex Environments via Off-Line Model Reduction and Real-Time Optimal Control

通过离线模型简化和实时最优控制，生成复杂环境中腿部运动的不对称步态

基本信息

批准号：
2128568
负责人：
Pranav Bhounsule
金额：
$ 49.97万
依托单位：
University of Illinois at Chicago
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 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2128568&HistoricalAwards=false
关键词：
Asymmetric Gait Generation Legged Locomotion

项目摘要

This Foundational Research in Robotics (FRR) project will create new control tools to improve the locomotion capabilities of legged robots in real-world environments. The goal is a generalizable and broadly applicable control framework for legged robots with highly articulated limbs. These new control tools will address the complexity of the robots, the hybrid dynamics caused by intermittent ground contact, and the limited control authority provided by small motors. Although current humanoid robots are highly proficient at moving at a constant speed in a straight line, they can be challenged in situations requiring unanticipated changes in speed and direction. Overcoming this challenge will facilitate the broader adoption of legged robots for mainstream applications in homes, offices, factories, and warehouses. This project will also train the next generation of engineers and roboticists through undergraduate research, capstone projects, and robotics outreach to minorities in Science, Technology, Engineering, and Mathematics.The most extensively investigated control approach for legged robots is to use symmetric force/torque profiles, which leads to symmetric gaits characterized by a constant speed, straight-line movement. However, to move at variable speed and to steer, robots need to use asymmetric torque/force profiles, which leads to asymmetric gaits. The high degrees of freedom of the legged system makes asymmetric gait generation to be computationally demanding and the underactuation (fewer actuators than degrees of freedom) makes gait stabilization to be challenging. The central idea of the grant is to use data-driven methods to approximate the dynamics between key instances in the gait. These approximations are done with low-order polynomials and they capture the asymmetry of the gaits. These reduced-order models, when incorporated within an optimization framework, can be solved in real-time. Finally, extensive experimental verification and validation is planned on a high-dimensional bipedal robot in real-world scenarios. 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.

这项机器人技术（FRR）项目的基础研究将创建新的控制工具，以提高现实环境中腿部机器人的运动能力。该目标是针对具有高度铰接的腿部机器人的可推广且广泛的控制框架。这些新的控制工具将解决机器人的复杂性，间歇性地面接触引起的混合动力以及小型电动机提供的有限控制权。尽管当前的人形机器人在直线上以恒定速度移动，但在需要速度和方向的意外变化的情况下，它们可能会受到挑战。克服这一挑战将有助于更广泛地采用腿部机器人在家庭，办公室，工厂和仓库中的主流应用程序。该项目还将通过本科生研究，顶峰项目和机器人技术向科学，技术，工程和数学的少数民族宣传来培训下一代工程师和机器人。轮廓，导致对称步态的特征是恒定速度，直线运动。但是，要以可变速度移动并转向，机器人需要使用不对称的扭矩/力剖面，从而导致步态不对称。腿部系统的高度自由度使得不对称的步态产生在计算上是苛刻的要求，而未成年人（少于自由度的执行器）使步态稳定变得具有挑战性。赠款的核心思想是使用数据驱动的方法来近似步态关键实例之间的动态。这些近似是用低阶多项式完成的，它们捕获了步态的不对称性。这些还原的模型在将其纳入优化框架中时，可以实时解决。最后，计划在现实世界中的高维双足机器人上进行广泛的实验验证和验证。该项目得到了机器人技术计划的跨指导基础研究的支持，该项目由工程局（ENG）以及计算机和信息科学与工程（CISE）共同管理和资助。该奖项反映了NSF的法定任务，并被认为是值得的。通过基金会的智力优点和更广泛的影响评估标准通过评估来支持。