Control of Robots that Move by Leaping, Bouncing, and Swinging

控制跳跃、弹跳和摆动的机器人

• 批准号: 1436297
• 负责人: Kevin Lynch
• 金额: $ 35万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1436297&HistoricalAwards=false
• 关键词: Control; Robots; Move; Leaping; Bouncing

A wide variety of robotic tasks, including locomotion and manipulation, can be characterized by switches between different sets of contact conditions. For example, a biped running robot can have its left foot on the ground, its right foot on the ground, or no feet on the ground. The equations of motion of the robot, which govern how the forces and torques of the motors at the robot's joints cause the robot to move, change as the robot changes contacts with the ground. These switching equations raise a number of open questions in motion planning and control for dynamically locomoting legged robots, such as robotic pack mules being tested by the US Army and a new generation of humanoid robots being developed around the world. Control theory, the basis of the lowest-level software that controls these robots, has not kept up with the latest developments in robot design. This research will narrow that gap, providing a firm theoretical "footing" for the software controlling dynamically locomoting robots. This will help realize the vision of legged robots in military, service, and home applications. The research will also provide opportunities for undergraduates and graduate students to demonstrate their work at the Chicago Museum of Science and Industry, influencing the next generation of scientists and engineers.This project focuses on the management of energy, momentum, and uncertainty for uncertain hybrid mechanical control systems with impacts. While the classical goal of robot motion control is to control the state of the robot with zero uncertainty, this research deals explicitly with the fact that this goal is idealized for all uncertain hybrid systems with impact and formally impossible for many due to their underactuation. The methodology applies to a broad class of Lagrangian control systems with impacts, with a focus on locomotion systems. The work will establish establish principles of state belief propagation and filtering, belief controllability, motion planning, and feedback control for systems with the structure of uncertain hybrid mechanical systems with impacts.

各种各样的机器人任务，包括运动和操纵，都可以通过不同接触条件组之间的切换来表征。 例如，双足跑步机器人可以左脚着地，右脚着地，或者没有脚着地。 机器人的运动方程控制机器人关节处电机的力和扭矩如何导致机器人移动，随着机器人与地面接触的变化而变化。 这些切换方程在动态移动腿式机器人的运动规划和控制方面提出了许多悬而未决的问题，例如美国陆军正在测试的机器人驮骡和世界各地正在开发的新一代人形机器人。 控制理论是控制这些机器人的最低级软件的基础，但它并没有跟上机器人设计的最新发展。 这项研究将缩小这一差距，为控制动态运动机器人的软件提供坚实的理论“基础”。 这将有助于实现腿式机器人在军事、服务和家庭应用中的愿景。 该研究还将为本科生和研究生提供在芝加哥科学与工业博物馆展示他们的工作的机会，影响下一代科学家和工程师。该项目重点关注不确定混合机械的能量、动量和不确定性的管理有影响的控制系统。 虽然机器人运动控制的经典目标是以零不确定性控制机器人的状态，但这项研究明确涉及这样一个事实：该目标对于所有具有影响力的不确定混合系统来说是理想化的，并且由于其驱动不足而对于许多系统来说在形式上是不可能的。 该方法适用于一系列具有影响的拉格朗日控制系统，重点关注运动系统。 这项工作将为具有影响的不确定混合机械系统结构的系统建立状态信念传播和过滤、信念可控性、运动规划和反馈控制的原理。