研究无人机旋翼下洗对柔性机械臂的干扰，提升空中操作精度
An Experimental Study of Downwash Effects on a Continuum Manipulator Integrated with a Multirotor UAV
- 用实验量化下洗导致机械臂末端位姿偏差
- 下洗使垂直位置和偏航角偏差最大，地面效应加剧
- 提出基于高斯过程的残差模型，定位误差降低89%以上
连续体机械臂飞行操作系统结合了柔性机械臂的顺应性与灵巧性，适用于狭窄或危险环境中的任务，但旋翼下洗会显著影响其性能，尤其是在靠近墙壁或地面时。目前尚未有针对连续体机械臂的下洗效应研究。本文通过实验研究了一种由绳索驱动的连续体机械臂在多旋翼平台上的下洗诱导运动学偏差。在无风条件下，将实际机械臂表现与恒曲率（CC）模型进行对比；在自由空间中，于四个电机油门档位下量化末端执行器相对于无风基准的位姿偏差，并在最大油门下靠近墙壁和地面时进行测试。结果表明，垂直位置和偏航角偏差最为显著，且地面效应进一步放大了这些偏差。基于实验数据训练了一个以恒曲率模型为引导的高斯过程回归（GPR）残差模型，使得正向位姿预测均方根误差（RMSE）在位置上降低89%-95%，姿态上降低47%-79%，为补偿下洗影响、实现面向支撑的下洗感知建模提供了有效方法。
原文摘要 · Abstract (English)
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.
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