利用空中机器人增强滑动性能：非驱动多轮构型的分析与解决方案
Enhancing Sliding Performance with Aerial Robots: Analysis and Solutions for Non-Actuated Multi-Wheel Configurations
AI总结：
针对配备非驱动多轮末端执行器的空中机器人滑动接触难题，本文结合物理实验构建高保真仿真器，并从机械设计准则与压力传感控制框架两方面提升其滑动性能与鲁棒性。
摘要：
空中机器人执行的滑动任务对于高处的检测和简单维护任务（如无损检测和喷涂）具有重要价值。尽管此类任务已采用各种末端执行器设计，但非驱动轮构型凭借其用于滑动运动的滚动能力、机械简单性和轻量化设计而得到更频繁的应用。此外，末端执行器设计中的非驱动多轮（多于一个轮子）构型允许在末端执行器尖端中心放置额外设备，例如用于应用的传感器和工具。然而，关于采用这种末端执行器设计的空中机器人在滑动过程中的关键接触条件，仍然缺乏研究。本文中，我们通过基于物理实验的深入分析，研究了与配备多个非驱动轮的空中机器人进行滑动操作相关的关键挑战。实验数据用于创建一个能够紧密捕捉真实世界条件的仿真器。我们从机械设计和控制两个角度提出解决方案，以提高空中机器人的滑动性能。从机械角度来看，设计准则由实验数据得出。从控制角度来看，我们引入了一种新颖的基于压力传感的控制框架，即使在滑动机动过程中也能确保可靠的任务执行。随后，所提方法的有效性和鲁棒性在所构建的仿真器中得到验证和比较，尤其是在高风险场景中。
英文摘要：
Sliding tasks performed by aerial robots are valuable for inspection and simple maintenance tasks at height, such as non-destructive testing and painting. Although various end-effector designs have been used for such tasks, non-actuated wheel configurations are more frequently applied thanks to their rolling capability for sliding motion, mechanical simplicity, and lightweight design. Moreover, a non-actuated multi-wheel (more than one wheel) configuration in the end-effector design allows the placement of additional equipment e.g., sensors and tools in the center of the end-effector tip for applications. However, there is still a lack of studies on crucial contact conditions during sliding using aerial robots with such an end-effector design. In this article, we investigate the key challenges associated with sliding operations using aerial robots equipped with multiple non-actuated wheels through in-depth analysis grounded in physical experiments. The experimental data is used to create a simulator that closely captures real-world conditions. We propose solutions from both mechanical design and control perspectives to improve the sliding performance of aerial robots. From a mechanical standpoint, design guidelines are derived from experimental data. From a control perspective, we introduce a novel pressure-sensing-based control framework that ensures reliable task execution, even during sliding maneuvers. The effectiveness and robustness of the proposed approaches are then validated and compared using the built simulator, particularly in high-risk scenarios.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
