Collaborative Research: Kinematic Reductions for Underactuated Mechanical Systems

合作研究：欠驱动机械系统的运动学简化

• 批准号: 0301567
• 负责人: Kevin Lynch
• 金额: $ 19万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0301567&HistoricalAwards=false
• 关键词: Collaborative; Research; Kinematic; Reductions; Underactuated

One of the most fundamental capabilities for an autonomous orsemi-autonomous robot system is the ability to quickly plan andreliably execute its own motions. We will study these fundamentalproblems for underactuated mechanical systems -- systems with feweractuators than degrees-of-freedom. Our interest in controlling thisclass of systems stems from two considerations. (1) It allowssoftware control redundancy (as opposed to mechanical or actuationredundancy) when one or more actuators of a fully actuated systemfails. (2) It is possible to design inexpensive mechanical systems byminimizing expensive mechanical elements such as actuators andtransmissions and replacing them with advanced control algorithms.We will explore a novel concept for mechanical control systems calledkinematic reductions. A kinematic reduction of a mechanical system isa first-order driftless system whose trajectories can be followed bythe second-order mechanical system. Kinematic reductions allowkinematic constraints (such as obstacles and joint limits) andactuator limits to be handled in a computationally efficient manner,allowing the possibility of real-time trajectory generation forunderactuated systems. Kinematic reductions encode the notion of``preferred'' motion directions for the system, allowing the plannedtrajectories to be followed quickly.To make full use of these properties of mechanical systems forreal-time trajectory generation and control, we will study a number ofopen issues. These include understanding when the kinematic reductionallows for closed-form calculation of motion plans for underactuatedsystems; adapting efficient kinematic motion planners from therobotics literature to kinematically controllable systems; localtrajectory optimization; feedback control to stabilize trajectories ofthe kinematic reductions; and implementation and validation of thecontrol strategies on an experimental vehicle. We also plan toexplore the role kinematic reductions will play in developingreduced-complexity hierarchical hybrid motion models.

自治的Orsemi-Autonanos机器人系统最基本的功能之一是能够快速计划雄心勃勃地执行自己的动议。 我们将研究这些针对不足的机械系统的基本问题 - 分离量少于自由度的系统。 我们对控制此系统的兴趣源于两个考虑因素。 （1）当一个或多个完全致动的系统拖网的执行器时，它允许软件控制冗余（而不是机械或致动还原）。 （2）可以通过将昂贵的机械元素（例如执行器和转移器）来设计廉价的机械系统，并用高级控制算法代替它们。我们将探索一个新颖的概念，用于机械控制系统，称为kinematic降低。 机械系统ISA一阶漂移系统的运动学还原，其轨迹可以在二阶机械系统之后进行。 运动学减少允许基因限制（例如障碍物和关节限制）和演员限制以计算上有效的方式处理，从而使实时轨迹生成进行实时实施系统的可能性。 运动学减少编码系统的“ PREFERRED”运动方向的概念，从而允许迅速遵循计划的设备。为了充分利用这些机械系统Forreal-time轨迹的产生和控制的这些属性，我们将研究许多开放的问题。 这些包括理解何时减少运动系统的封闭形式计算运动计划不足的运动计划；将有效的运动运动计划者从植物学文献调整到运动学可控系统； localTrajectory优化；反馈控制以稳定运动学减少的轨迹；以及实验工具上的策略的实施和验证。 我们还计划探索运动学减少的作用，将在开发雷神的复杂性层次混合运动模型中发挥作用。