RI: Small: Hierarchical Planning, Estimation, and Control for Hybrid Mechanical Systems

混合机械系统出现在许多应用中，包括与地面接触发生变化的跳跃、行走和攀登机器人；库仑摩擦导致粘滑行为的滑动转向车辆；以及与物体交互的假肢设备。所有这些应用都受到非线性、非平稳过渡和不确定性的影响，这些系统需要新的运动规划和控制工具，该工作利用机械系统的特定结构来限制不确定性的传播，并设计反馈控制器来最大化执行的健壮性。这项工作建立在运动规划和估计的最新技术基础上，包括基于样本和基于优化的规划，导致用于不确定混合机械系统的工具类似于用于线性系统的控制和估计工具。这些机器人包括1)猴子机器人，这是一种使用电磁铁和单一电机沿垂直墙壁移动的机器人；2)跑酷机器人，使用机械接触和跳跃来攀登狭窄的通道；3)滑行车辆，由于粘/滑摩擦效应而经历不连续的动力学。这项工作的所有阶段都包括本科生和少数民族学生的参与。除了在会议和期刊上传播外，成果还会在公众可见的维基上传播。

Hybrid mechanical systems arise in many applications, including hopping, walking, and climbing robots where contact with the ground changes; skid-steering vehicles where Coulomb friction introduces stick/slip behavior; and prosthetic devices that interact with objects. All of these applications are influenced by nonlinearity, nonsmooth transitions, and uncertainty, and these systems demand new tools in motion planning and control.This work takes advantage of the specific structure of mechanical systems to bound the propagation of uncertainty and to develop feedback controllers that maximize robustness of execution. The work builds on state-of-the-art techniques in motion planning and estimation, including sample-based and optimization-based planning, leading to tools for uncertain hybrid mechanical systems that are analogous to control and estimation tools used for linear systems.Example systems are used to drive algorithm development as well as to verify performance. These include 1) the Monkeybot, a robot that uses electromagnets and a single motor to locomote along a vertical wall;2) a parkour robot that uses mechanical contact and jumping to climb narrow passages; and 3) a skid-steered vehicle that experiences discontinuous dynamics due to stick/slip friction effects. All phases of this work include participation of undergraduates and minority students. In addition to dissemination in conferences and journals, results are disseminated on a publicly viewable wiki.