空中布局：用于天花板精确飞行中标记的柔顺驱动末端执行器的设计与控制
Aerial Layouting: Design and Control of a Compliant and Actuated End-Effector for Precise In-flight Marking on Ceilings
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中文总结 AI 辅助
该研究针对空中机器人毫米级定位精度需求，设计采用Gough-Stewart机构的柔顺驱动末端执行器，实现天花板上的精确标记，无需复杂建模或控制。
中文摘要 AI 辅助
空中机器人已展现出出色的精确控制能力，例如穿越障碍物的动态飞行或高度复杂的编排动作。尽管这些任务需要一定精度，但仍存在一些当今难以达到精度要求的问题，其中之一便是空中交互。空中机器人设计与控制的进步已使这类基于接触的任务成为可能，并推动了对具有挑战性的现实任务的研究，包括基于接触的检测。不过，对于检测任务而言，厘米级精度已足够且可实现；而对于其他任务，如建筑工地的布局或一般推滑任务，所需的定位精度为毫米级。为实现如此高的精度，我们提出一种新型空中系统，由一架飞行器和一个新型“智能”末端执行器组成，该执行器采用稳定性优化的Gough-Stewart机构。我们介绍其设计过程与特性，融入了柔顺性、多接触点、驱动性和自包含性的原则。实验中，我们验证了为新型末端执行器做出的设计选择对于获得所需定位精度是必要的。此外，我们证明无需对空中机器人进行精确建模或复杂控制，即可可靠地以毫米级精度在天花板上标记线条。
英文摘要
Aerial robots have demonstrated impressive feats of precise control, such as dynamic flight through openings or highly complex choreographies. Despite the accuracy needed for these tasks, there are problems that require levels of precision that are challenging to achieve today. One such problem is aerial interaction. Advances in aerial robot design and control have made such contact-based tasks possible and opened up research into challenging real-world tasks, including contact-based inspection. However, while centimetre accuracy is sufficient and achievable for inspection tasks, the positioning accuracy needed for other problems, such as layouting on construction sites or general push-and-slide tasks, is millimetres. To achieve such a high precision, we propose a new aerial system composed of an aerial vehicle equipped with a novel "smart" end-effector leveraging a stability-optimized Gough-Stewart mechanism. We present its design process and features incorporating the principles of compliance, multiple contact points, actuation, and self-containment. In experiments, we verify that the design choices made for our novel end-effector are necessary to obtain the desired positioning precision. Furthermore, we demonstrate that we can reliably mark lines on ceilings with millimetre accuracy without the need for precise modeling or sophisticated control of the aerial robot.
发表机构
- Autonomous Systems Lab, ETH Zurich（苏黎世联邦理工学院自主系统实验室）
机构由 AI 辅助整理，请以论文原文为准。
