Dynamically Dexterous Robots via Switched and Tuned Oscillators

通过开关和调谐振荡器实现动态灵巧机器人

• 批准号: 9510673
• 负责人: Daniel Koditschek
• 金额: $ 22.7万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-08-01 至 1999-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9510673&HistoricalAwards=false
• 关键词: Dynamically; Dexterous; Robots; via; Switched

The research involves empirical and theoretical inquiry into techniques for combining simple oscillators to produce new and more complex robot behaviors from existing simpler ones. Previously funded work in the PI's laboratory has already demonstrated that simple oscillators can be used to confer upon a robot superlative but narrow dynamical dexterity. The present study attempts to demonstrate that effective coupling techniques for such existing behavioral mechanisms can confer a much broader range of behavior. The empirical project addresses a robotic manipulation scenario termed ``Sensor Driven Dynamical Pick and Place.'' In this scenario, the robot uses a flat paddle to acquire balls thrown into the workspace; balance or bat them as required through a clutter; loft them into an out-of-reach destination receptacle; and resistunanticipated perturbations along the way. The recourse to oscillators reflects an almost exclusive theoretical focus on event driven manipulation. Such a commitment to feedback control addresses the fact that failures in machine reliability frequently occur because of events which are not intrinsically unrecoverable but which violate our models dramatically and cannot be anticipated. The focus on error detection and recovery in a dynamical setting brings into correspondence the concerns of the decade old (and still vigorously developing) fine motion planning literature and certain concepts and analytical tools from the century old (and still vigorously developing) dynamical systems literature that have proven useful in the PI's previously funded work.

这项研究涉及经验和理论调查技术相结合的简单振荡器，以产生新的和更多的 复杂的机器人行为从现有的简单 一个 PI实验室先前资助的工作已经证明，简单的振荡器可以用来赋予机器人最高级但范围有限的动力灵活性。 本研究试图证明，有效的耦合技术，这种现有的行为机制可以赋予更广泛的行为。该实证项目涉及一个 机器人操作场景称为“传感器驱动的动态拾取和放置”。"在这个场景中，机器人使用一个扁平的球拍来获取扔进工作区的球;根据需要通过杂乱的环境来平衡或击打它们;将它们放入一个无法到达的目的地容器;并抵抗沿途沿着的意外扰动。对振荡指标的依赖反映了对事件驱动操纵的几乎完全的理论关注。 这样的 对反馈控制的承诺解决了这样一个事实， 机器的可靠性经常发生， 并非本质上不可恢复，而是严重违反了我们的模型，无法预测。 在动态环境中对错误检测和恢复的关注对应于十年前（仍在大力发展）的精细运动规划文献和来自世纪前（仍在大力发展）的动力系统文献的某些概念和分析工具，这些文献已被证明在PI先前资助的工作中是有用的。