使用線上稀疏呈現的物件模型進行機器人並行追蹤與建圖

Robot Parallel Tracking and Mapping Using Online Sparse-representation Object Model

陳國瑋(Kuo-Wei Chen)

指導教授 ： 王銀添

淡江大學/工學院/機械與機電工程學系碩士班/碩士(2012年)

https://doi.org/10.6846/TKU.2012.00550

摘要

本論文針對視覺式動態環境中同時定位、建圖與移動物體追蹤的研究議題，探討使用移動攝影機偵測與追蹤移動物體之任務。主要研究議題包括發展線上建立物件模型以及偵測與追蹤移動物體等演算法。偵測明顯的影像特徵點做為線上建模之訓練資料，以便建立稀疏呈現的物件模型。比對環境中的影像特徵與物件模型的元件，以辨識物體與搜尋物體的位置。發展的演算法再結合移動物體偵測、狀態估測方法、與視覺式感測等技術，完成以移動攝影機偵測與追蹤移動物體。整合的系統將可以應用在行動機器人、輪椅、汽車、與飛行機器人之上，執行動態環境中並行追蹤移動物體與建圖的任務。

關鍵字

並行追蹤與建圖 ； 線上物件模型 ； 狀態估測 ； 視覺式感測

並列摘要

This thesis presents an algorithm of moving object detection and tracking for robot concurrently localization, mapping and moving object tracking in dynamic environment. The major research topics include on-line object model construction as well as moving object detection and tracking. Apparent image features are detected and utilized as the training data for on-line constructing and sparse representing the object model. After the object model is constructed, the model elements are further matched with the image features obtained from the environment in order to recognize the object and search the object position in image and cartesian spaces. Furthermore, the developed algorithm is integrated with the methods of moving object detection, state estimation, and visual sensing to develop a system which is capable of tracking moving objects using moving camera. The detecting and tracking method developed in this thesis is capable of being applied in many systems such as mobile robot, wheelchair, car, and aerial robot to implement the tasks of parallel tracking and mapping in dynamic environments.

並列關鍵字

Parallel Tracking and Mapping (PTAM) ； On-Line Object Model ； State Estimation ； Visual Sensing

參考文獻

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