Simulation-Based 3D Pose Estimation Using a Depth Camera
| Autor: | Jie-Hung Wang, 王傑鴻 |
|---|---|
| Rok vydání: | 2016 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 104 Object recognition and posture estimate play an important role in apply of automatic assembly and service robot. Today, the most popular method of recognition is using geometric or feature statistics further identify the object and estimate the posture by comparison of CAD model and point cloud of object by scanning. However, due to the infrared ray’s sensing parallax effect of Kinect sensor, causes significant distortion of point cloud information. In order to improve the efficacy of feature comparison of distortion point cloud data and object’s CAD model. We propose a Kinect virtual simulation space comparison method, can simulate the Kinect scan situation by estimate the sight angle, object distance and the intensity of environment parameters. The point cloud similarity can be increase by this method. So, it can precisely and rapidly achieve object comparison and picking posture estimation. Compare with the previous research, the result of this study reveal that, the accuracy of posture estimation and efficacy of operation power has significant increase. This technique will help automatic assembly and service robot field has more application of immediacy and accuracy. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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