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RI: Small: Agile Legged Robots: Composing Periodic Gaits for Aperiodic Locomotion

RI：小型：敏捷腿式机器人：为非周期性运动组合周期性步态

基本信息

批准号：
1946282
负责人：
Pranav Bhounsule
金额：
$ 35.1万
依托单位：
University of Illinois at Chicago
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-16 至 2023-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1946282&HistoricalAwards=false
关键词：
RI Small Agile Legged Robots

项目摘要

The overall objective of this project is to create computational algorithms for legged agility, which is defined as the robots ability to change its speed, direction, and/or gait (e.g., walk to run). As evident from biology, legs provide a highly agile mode of locomotion, yet no legged robot has been able to achieve performance comparable to highly performing humans or animals. The continued existence of this need is an important problem because it limits the usefulness of legged robots; the need to start, stop, change directions, accelerate/decelerate quickly are all essential if legged robots are to replace wheeled robots in rough terrain. Some applications of such agile robots are, as first responders, as search and rescue personnel, and as industrial workers. In addition, this research will provide training opportunities for multiple undergraduate students and outreach to school children including target populations that are traditionally under-represented in Science, Technology, Engineering, and Mathematics (STEM). The key idea to achieve agility is to combine steady-state (periodic) gaits to achieve non-steady gaits. The rationale is that computation-wise, steady-state gaits are at least an order of magnitude cheaper to compute than non-steady gaits. The specific aims of this research are to create tools for (1) filling the entire state space with steady-state gait controllers and associated stabilizing controllers, (2) transitioning between steady-state gaits to create agile gaits and (3) experimental validation of the approach. A novel formulation of the Lyapunov function allows the creation of stabilizing controllers and estimating the regions of attraction (ROA). Then these ROAs will be composed sequentially based on their overlapping regions to create transition controllers for agile locomotion.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.

该项目的总体目标是创建腿部敏捷性的计算算法，腿部敏捷性被定义为机器人改变其速度、方向和/或步态的能力（例如，步行跑步）。从生物学上可以看出，腿提供了一种高度敏捷的运动模式，但没有腿机器人能够达到与高性能人类或动物相媲美的性能。这种需求的持续存在是一个重要的问题，因为它限制了腿式机器人的实用性;如果腿式机器人要在崎岖的地形中取代轮式机器人，则需要快速启动、停止、改变方向、加速/减速。这种敏捷机器人的一些应用是，作为第一响应者，作为搜索和救援人员，以及作为工业工人。此外，这项研究将为多名本科生提供培训机会，并与包括传统上在科学，技术，工程和数学（STEM）中代表性不足的目标人群在内的在校儿童进行外联。实现敏捷性的关键思想是将联合收割机稳态（周期性）步态与非稳态步态相结合。其基本原理是，计算明智的，稳态步态至少是一个数量级的计算比非稳态步态便宜。本研究的具体目标是创建工具（1）用稳态步态控制器和相关的稳定控制器填充整个状态空间，（2）在稳态步态之间过渡以创建敏捷步态，以及（3）实验验证该方法。一种新的制定的李雅普诺夫函数允许创建的稳定控制器和估计的区域的吸引力（罗阿）。然后，这些ROA将根据它们的重叠区域依次组成，以创建敏捷运动的过渡控制器。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。