應用於無人載具任務之單眼視覺式目標物定位

Abstract

本篇論文提出一個MVTL視覺式定位技術演算法，可針對無人載具所偵測到的目標物執行三度空間目標定位，MVTL是來自於Monocular Vision-based Target Localization的縮寫，本技術是藉由整合光學式編碼器、電子羅盤及單眼攝影機等不同的裝置來實現，基於運動模式及連續影像，吾人藉由使用卡曼濾波器(Extended Kalmam Filter, EKF)演算法來估計目標位置，所提出的定位方式是相當符合實際運用，因為關於事先放置已知尺寸人工地標物，在本論文的演算法是不需要的，本篇技術特別適用於機器人的室內導航及目標定位以及具有相當高可能性延伸應用於使用空用里程裝置的空用無人載具(Unmanned Aerial Vehicle, UAV)之巡視及監測任務，最後，實驗證明於室內環境載具在高速移動狀態下，目標物定位可達“公分”級之精確度。

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.