發(fā)布時間：2019-01-17 08:09

【摘要】：近年來,隨著智能化進程加快,服務機器人技術得到了飛速發(fā)展。物品識別與定位技術作為智能服務機器人必備功能,正逐漸成為研究熱點。精準的物品識別和定位能力是機器人執(zhí)行指定任務的先決條件,在日常生活中有著廣泛的應用,如倒水、做飯、拖地等等。傳統(tǒng)的物品識別與定位方法多是基于二維RGB圖像,根據物品在顏色圖像中呈現(xiàn)的諸多特征來進行識別和定位。雖然這些方法取得了不錯的效果,但是由于物品的天然特性是三維,無論是形狀識別還是6自由度位姿估計都需要充足的空間信息。所以,本文將二維RGB圖像數(shù)據和三維點云數(shù)據相結合,提出了基于RGB-D數(shù)據的物品識別與定位方法。文中首先介紹了物品模型數(shù)據庫的建立過程,通過使用KinectV2傳感器分別采集物品的二維和三維數(shù)據來構建數(shù)據庫。然后,在二維RGB圖像數(shù)據下提取SURF特征,對場景中的物品進行初識別。之后,將初識別的結果映射到三維點云數(shù)據下,并使用最小割方法將物品點云從場景中分割出來。最后使用VFH描述子進行物品的精確識別和6自由度位姿估計。此外,為了得到更精確的定位,又提出結合點云配準的6自由度位姿估計方法。實驗表明,本方法有效可行。
[Abstract]:In recent years, with the acceleration of intelligent process, service robot technology has been rapid development. As an essential function of intelligent service robot, the technology of object identification and location is becoming a research hotspot. Accurate object recognition and location is a prerequisite for robots to perform assigned tasks, and it has been widely used in daily life, such as pouring water, cooking, mopping and so on. The traditional methods of object recognition and localization are based on two-dimensional RGB images, which are based on many features of objects in color images. Although these methods have achieved good results, due to the natural characteristics of the object is three-dimensional, both shape recognition and 6-DOF pose estimation need sufficient spatial information. Therefore, this paper combines 2D RGB image data with 3D point cloud data, and proposes an object recognition and location method based on RGB-D data. In this paper, the process of building the object model database is introduced, and the database is constructed by using the KinectV2 sensor to collect the 2D and 3D data of the object respectively. Then, SURF features are extracted from two-dimensional RGB images, and the objects in the scene are first identified. After that, the initial recognition results are mapped to 3D point cloud data, and the item point cloud is segmented from the scene using the minimum cut method. Finally, the VFH descriptor is used to identify the object accurately and estimate the position and pose of 6 degrees of freedom. In addition, in order to obtain more accurate location, a 6-DOF position and attitude estimation method of combining point cloud registration is proposed. Experiments show that this method is effective and feasible.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41
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本文編號：2409796