多旋翼无人机集成的连续体机械臂下洗效应的实验研究
An Experimental Study of Downwash Effects on a Continuum Manipulator Integrated with a Multirotor UAV
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中文总结 AI 辅助
本文针对多旋翼无人机集成的连续体机械臂，通过实验研究了螺旋桨下洗对其位姿的影响，提出CC引导的GPR残差模型可显著提升位姿预测精度，为相关系统的下洗补偿建模提供了方法。
中文摘要 AI 辅助
连续体机械臂空中操纵系统利用软机械臂的柔顺性和灵活性，可在狭窄或危险环境中执行任务，但螺旋桨下洗会降低其性能，尤其在靠近墙壁和地面时。目前针对连续体机械臂的该效应尚未得到表征。本文对集成了多旋翼平台的腱驱动连续体机械臂开展实验，研究下洗诱导的运动学偏差。在静止空气条件下，将连续体机械臂（CM）与常曲率（CC）模型进行对比；随后在自由空间的四个螺旋桨油门等级下，以及最大油门且靠近墙壁、靠近地面的场景中，量化下洗诱导的末端执行器位姿相对于静止空气实验基线均值的偏差。结果表明，垂直位置和偏航的偏差最大，且会被地面效应放大。从实验数据中学习得到一种CC引导的高斯过程回归（GPR）残差模型，该模型可将正向位姿预测的均方根误差（RMSE）降低89%-95%（位置）和47%-79%（方向），为连续体机械臂空中操纵系统提供了支持补偿的、感知下洗的建模方法。
英文摘要
Continuum arm aerial manipulation systems leverage soft-manipulator compliance and dexterity for tasks in confined or hazardous environments, but propeller downwash can degrade performance, particularly near walls and the ground. This effect remains uncharacterized for continuum manipulators. This letter experimentally studies downwash-induced kinematic deviations of a tendon-driven continuum manipulator integrated with a multirotor platform. Under still-air conditions, the CM is compared with a constant-curvature (CC) model. Downwash- induced end-effector pose deviations are then quantified relative to the mean still-air experimental baseline at four propeller throttle levels in free space, and at maximum throttle near a wall, and near the ground. Vertical position and yaw show the largest deviations and are amplified by ground effect. A CC-guided Gaussian process regression (GPR) residual model is learned from experimental data that improves forward pose prediction RMSE (position by 89-95%, orientation by 47-79%), and support compensation-oriented, downwash-aware modeling of continuum arm aerial manipulation systems.
发表机构
- Queensland University of Technology (QUT)（昆士兰科技大学）
- QUT Centre for Robotics（昆士兰科技大学机器人中心）
- Research Engineering Facility (REF)（研究工程设施）
- School of Electrical Engineering and Robotics（电气工程与机器人学院）
机构由 AI 辅助整理，请以论文原文为准。
