Monocular Vision-based Target Localization for Mobile Vehicle Tasks

• Main Authors: Lu, Wang-Chuan, 呂旺全
• Other Authors: Wu, Bing-Fei
• Format: Others
• Language: en_US
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/43734967459036160787

碩士 === 國立交通大學 === 電機學院電機與控制學程 === 99 === In this paper, MVTL algorithm presents a vision-based technology for localizing targets in 3D environment which have to be detected by a mobile vehicle. MVTL is abbreviated from Monocular Vision-based Target Localization. This is achieved by the combination of different types of sensors including optical wheel encoders, an electrical compass and visual observations with a single camera. Based on the motion model and image sequences, we employ an extended Kalman filter (EKF) to estimate target locations. The proposed localization system is applicable in practice because it is not necessary to have the initializing setting regarding starting the system from artificial landmarks of known size. The technique is especially suitable for navigation and target tracing for an indoor robot and has a high potential extension to surveillance and monitoring for UAVs (Unmanned Aerial Vehicles) with aerial odometry sensors. The experimental results present “cm” level accuracy of the localizations of the targets in indoor environment under a high speed vehicle movement.