CAREER: Using Multiple Gaits and Inherent Dynamics for Legged Robots With Improved Mobility
CAREER: Using Multiple Gaits and Inherent Dynamics for Legged Robots With Improved Mobility
批准号:
1453346
负责人:
C. David Remy
金额:
$50.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-03-01 至 2020-02-29
中文摘要
这个教师早期职业发展(CAREER)计划项目的目标是研究更快,更高效的腿式机器人。 该项目利用了目前尚未开发的在不同运动速度下使用不同步态的可能性。 这个想法是受大自然的启发。 例如,当人类提高速度时,他们会从步行转变为跑步;马会从步行转变为小跑和飞奔。 转换步态类似于在汽车中转换档位。 它增加了多功能性并降低了能耗。 此外,在自然界中,步态的选择与动物的形态密切相关。 一只巨大的大象和一只花丝瞪羚的移动方式不同。 这个项目将研究步态,运动和形态的复杂关系,并将基本原理转移到机器人系统。 这项工作将在模拟研究和实际机器人中进行。 从长远来看,该职业计划旨在开发达到甚至超过人类和动物敏捷性的机器人。 它将使我们能够制造出像猎豹一样跑得快、像哈士奇一样耐力强的机器人,同时像山羊一样掌握地形。 此外,它将为我们提供主动假肢和外骨骼的新设计。 该项目还将利用腿部运动的迷人主题来激发K-12学生,代表性不足的群体以及更广泛的科学,技术和工程受众的兴趣。该项目旨在了解设计,建造和控制腿部机器人的基本原理,并利用其固有的机械动力学。 基本前提是,运动可以在很大程度上被动地从惯性,重力和弹性振荡的相互作用中出现。 这个项目的目标是确定系统中,这种动态可以激发在各种不同的模式。 不同的模式将对应于不同的步态,并且将使得能够在不同的操作条件下进行有效的运动。 这项工作将扩展最优控制和机器学习技术,如多重射击,直接搭配或概率直接策略学习方法,以允许同时生成步态,运动和形态参数(包括刚度值,质量分布或致动器尺寸)。 由于速度、效率、鲁棒性和敏捷性等性能标准只能在实际硬件实现中充分体现出来,因此研究团队不仅将在仿真中研究这些概念,还将使用硬件原型来研究这些概念。 特别是,该方法将被用来检查灵活的脊椎在四足动物和关节踝关节在两足动物的好处,以及比较系列弹性驱动和并行弹性驱动的概念。
英文摘要
The goal of this Faculty Early Career Development (CAREER) Program project is to investigate legged robots that are faster and energetically more efficient. The project capitalizes on the currently untapped possibility of using different gaits at different locomotion speeds. This idea is inspired by nature. Humans, for example, switch from walking to running as they increase speed; horses transit from walking to trotting and galloping. Switching gaits is analogous to switching gears in a car. It increases versatility and reduces energy consumption. Additionally, in nature the choice of gaits is strongly coupled to an animal's morphology. A massive elephant moves differently than a filigree gazelle. This project will investigate this complex relation of gaits, motions, and morphologies, and will transfer the underlying principles to robotic systems. The work will be conducted in simulation studies and with actual robots. In the long term, this CAREER plan aims at the development of robots that reach and even exceed the agility of humans and animals. It will enable us to build robots that can run as fast as a cheetah and as enduring as a husky, while mastering the same terrain as a mountain goat. Moreover, it will provide us with novel designs for active prosthetics and exoskeletons. The project will also leverage the fascinating topic of legged locomotion to spark the interest of K-12 students, underrepresented groups, and a broader audience for science, technology, and engineering.This project seeks to understand the fundamental principles of designing, building, and controlling legged robots that embrace and exploit their inherent mechanical dynamics. The underlying premise is that locomotion can emerge in great part passively from the interaction of inertia, gravity, and elastic oscillations. The goal of this project is to identify systems in which such dynamics can be excited in a variety of different modes. Different modes would correspond to different gaits, and would enable efficient motion in different operational conditions. The work will extend optimal control and machine-learning techniques, such as multiple shooting, direct collocation, or probabilistic direct policy learning methods, to allow the simultaneous generation of gaits, motions, and morphological parameters (including stiffness values, mass distributions, or actuator sizes). Since performance criteria such as speed, efficiency, robustness, and agility only fully manifest themselves in actual hardware implementations, the research team will study these concepts not only in simulation, but also with hardware prototypes. In particular, the methodology will be employed to examine the benefits of flexible spines in quadrupeds and of articulated ankles in bipeds, as well as to compare series elastic actuation and parallel elastic actuation concepts.
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海外基金
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依托单位: