标题: 智慧型轮椅机器人基于多感测器融合之远距离人员侦测与追踪
Multisensor Fusion Based Large Range Human Detection and Tracking for Intelligent Wheelchair Robots
作者: 邹岱佑
Tsou, Tai-Yu
吴炳飞
Wu, Bing-Fei
电控工程研究所
关键字: 扩展卡曼滤波器;同步定位与地图建立;加速稳健性特征辨识;extended Kalman filter, EKF;simultaneous localization and map building, SLAM;Speeded Up Robust Feature, SURF
公开日期: 2013
摘要: 近几年因人口老化,如何提升年长者或须以轮椅代步者的自主行动能力,并减轻伴随者的负担,即成为十分重要的课题。基于此因,轮椅型机器人增加了智慧型的功能。它提供人员辨识与跟随的功能,这项功能的加强,使得轮椅不再只是轮椅,而成为最好的辅助工具并陪伴者。本论文提出利用多感测器融合远距离人员侦测与追踪的服务。首先本研究使用雷射感测器与惯性感测器配合扩展卡曼滤波器(extended Kalman filter, EKF)来做同步定位与地图建立(simultaneous localization and map building, SLAM),并且为了增加人员跟随的强健性,本研究还使用了雷射感测器与影像的感测资讯,一开始利用雷射感测器来侦测人员区间,再使用PTZ摄影机藉由加速稳健性特征辨识(Speeded Up Robust Feature, SURF)来区别辨识所要跟随的人员。本系统利用PTZ摄影机能放大焦距与雷射雷达可侦测远距离的特性,配合所建立的地图完成远距离的人员跟随之功能。仅此,以此论文展示本实验的成果。
Recently, several robotic wheelchairs have been proposed that employ autonomous functions. In designing wheelchairs, it is important to reduce the accompanist load. To provide such a task, the mobile robot needs to recognize and track people. In this paper, we propose to utilize the multisensory data fusion to track a target accompanist. First, the simultaneous localization and map building is achieved by using the laser range finder (LRF) and inertial sensors with the extended Kalman filter recursively. To track the target person robustly, the accompanist, are tracked by fusing laser and vision data. The human objects are detected by LRF, and the identity of accompanist is recognized using a PTZ camera with a pre-defined signature using the speeded up robust features algorithm. The proposed system can adaptively search visual signature and track the accompanist by dynamically zooming the PTZ camera based on LRF detection results to enlarge the range of human following. The experimental results verified and demonstrated the performance of the proposed system.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT070060003
http://hdl.handle.net/11536/73210
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