RGB-D sensor based SLAM and human tracking with Bayesian framework for wheelchair robots

Bing-Fei Wu, Cheng Lung Jen, Wun Fang Li, Tai Yu Tsou, Pin Yi Tseng, Kai Tse Hsiao

研究成果: Conference contribution同行評審

17 引文 斯高帕斯(Scopus)

摘要

In this paper, we present an approach to visual SLAM and human tracking for a wheelchair robot equipped with a Microsoft Kinect sensor that which is a novel sensing system that captures RGB and depth (RGB-D) images simultaneously. The speeded-up robust feature (SURF) algorithm is employed to provide the robust description of feature for environments and the target person from RGB images. Based on the environmental SURF features, we present the natural landmark based simultaneous localization and mapping with the extended Kalman filter suing RGB-D data. Meanwhile, a depth clustering based human detection is proposed to extract human candidates. Accordantly, the target person tracking is achieved with an online learned RGB-D appearance model by integrating histogram orientation of gradient descriptor, color, depth, and position information from the body of the identified caregiver. Moreover, a fuzzy based controller provides dynamical human following for the wheelchair robot with a desired interval. Consequently, the experimental results demonstrated the effectiveness and feasibility in real world environments.

原文English
主出版物標題2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013 - Conference Proceedings
頁面110-115
頁數6
DOIs
出版狀態Published - 9 九月 2013
事件2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013 - Tainan, Taiwan
持續時間: 3 五月 20132 六月 2013

出版系列

名字2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013 - Conference Proceedings

Conference

Conference2013 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2013
國家Taiwan
城市Tainan
期間3/05/132/06/13

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