EVPeriscope：基于事件螺旋桨跟踪的空中与地面车辆扩展感知

中文摘要 AI 辅助

可靠的空中与地面机器人之间的相对定位是紧密协调异构团队的关键要求。使用传统的基于帧的相机和基准标记可能难以实现这一点，因为它们对运动模糊、光照变化和载荷限制敏感。本文提出EVPeriscope，一种基于事件的感知系统，通过在地面机器人上使用朝上的事件相机检测四旋翼螺旋桨的高频视觉特征，实现对四旋翼的检测、定位和控制。当机载传感器出现退化或遮挡时，该系统允许四旋翼作为地面机器人的扩展感知系统。我们通过在风速高达15英里/小时的具有挑战性的野外条件下，在白天和夜间进行的实验，展示了这种有袋式地面-空中系统的能力。我们表明，该系统支持在茂密植被中通过地面机器人传感器被遮挡的区域进行定位和闭环导航。我们的四旋翼控制系统以200赫兹的频率运行，完全依靠机载传感和计算。更多细节和实验视频可在项目页面上找到：此https URL。

英文摘要

Reliable relative localization between aerial and ground robots is a key requirement for tightly coordinated heterogeneous teams. This can be difficult to do using conventional frame-based cameras and fiducial markers because they are sensitive to motion blur, lighting variations, and payload constraints. This paper presents EVPeriscope, an event-based perception system that enables detection, localization and control of a quadrotor using an upward-facing event camera on a ground robot by detecting the high-frequency visual signature of its propellers. This system allows the quadrotor to function as an extended perception system for the ground robot when onboard sensors exhibit degradation or occlusion. We demonstrate the capabilities of this marsupial ground-aerial system via experiments in challenging field conditions with wind speeds of up to 15 mph, in both daylight and at night. We show that the system supports localization and closed-loop navigation through dense foliage where the ground robot's sensors are occluded. Our control system for the quadrotor operates at 200 Hz entirely with onboard sensing and computation. More details and experiment videos can be found on the project page: https://ongdexter.github.io/evperiscope.

发表机构

• University of Pennsylvania（宾夕法尼亚大学）

机构由 AI 辅助整理，请以论文原文为准。