一种用于室内飞艇的微型基于视觉的定位系统
A Miniature Vision-Based Localization System for Indoor Blimps
AI总结：
针对室内飞艇自主定位需求，提出基于Superpoint特征与运动恢复结构的微型视觉定位系统，通过单目相机和WiFi传输数据至地面端运算，可将遥控室内飞艇升级为自主飞艇，适用于多类室内场景。
摘要：
随着飞艇研究受到越来越多的关注，笔者希望构建一款可与人类交互的室内飞艇。作为起步，笔者提出开发一套视觉定位系统，使飞艇能够在室内环境中自主完成自身定位。该系统首先采用结合Superpoint视觉特征的运动恢复结构（Structure from Motion）技术重建室内环境。随后，借助预先构建的稀疏点云地图，系统通过对从地图中观测到的匹配视觉特征持续进行位姿估计，生成相机位姿。在本项目中，飞艇仅作为约束感知系统重量的参考移动平台。感知系统包含一个单目相机和一个WiFi适配器，用于捕获视觉数据并将其传输至运行算法的地面PC站。本项目的成功将把遥控室内飞艇转变为自主室内飞艇，可应用于 surveillance、广告、室内建图等场景。
英文摘要：
With increasing attention paid to blimp research, I hope to build an indoor blimp to interact with humans. To begin with, I propose developing a visual localization system to enable blimps to localize themselves in an indoor environment autonomously. This system initially reconstructs an indoor environment by employing Structure from Motion with Superpoint visual features. Next, with the previously built sparse point cloud map, the system generates camera poses by continuously employing pose estimation on matched visual features observed from the map. In this project, the blimp only serves as a reference mobile platform that constrains the weight of the perception system. The perception system contains one monocular camera and a WiFi adaptor to capture and transmit visual data to a ground PC station where the algorithms will be executed. The success of this project will transform remote-controlled indoor blimps into autonomous indoor blimps, which can be utilized for applications such as surveillance, advertisement, and indoor mapping.
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。
