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

各种各样的机器人任务，包括运动和操纵，可以通过不同的接触条件之间的切换来表征。 例如，一个跑步机器人可以让它的左脚在地上，右脚在地上，或者没有脚在地上。 机器人的运动方程决定了机器人关节处电机的力和力矩如何使机器人移动，随着机器人与地面接触的变化而变化。 这些切换方程提出了一些开放的问题，在运动规划和控制的动态腿式机器人，如机器人包骡子正在测试的美国陆军和新一代的人形机器人正在世界各地开发。 控制理论是控制这些机器人的最底层软件的基础，它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，为软件控制动态移动机器人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机会，在芝加哥科学与工业博物馆展示他们的工作，影响下一代科学家和工程师。本项目重点研究具有冲击的不确定混合机械控制系统的能量、动量和不确定性的管理。 虽然机器人运动控制的经典目标是控制机器人的状态与零不确定性，本研究明确处理的事实，这一目标是理想化的所有不确定的混合动力系统的影响和正式不可能的许多，由于他们的欠驱动。 该方法适用于广泛的一类拉格朗日控制系统的影响，重点是运动系统。 本论文的工作将建立具有碰撞不确定混合机械系统结构的系统的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。

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.