Robust 3D Indoor Map Building via RGB-D SLAM with Adaptive IMU Fusion on Robot
文献类型：会议论文
| 作者 | Meng XR(孟馨蕊)1,2 ; Gao W(高伟)1,2; Hu ZY(胡占义)1,2
|
| 出版日期 | 2018 |
| 会议日期 | 2017.9 |
| 会议地点 | 上海 |
| 关键词 | Camera Pose Estimation Rgb-d Slam Imu Robot Movement Pattern Calibration |
| 页码 | 454-465 |
| 英文摘要 | Building a 3D map of indoor environment is a prerequisite for various applications, ranging from service robot to augmented reality, where RGB-D SLAM is a commonly used technique. To efficiently and robustly build a 3D map via RGB-D SLAM on robot, or the RGB-D sensor mounted on a moving robot, the following two key issues must be addressed: How to reliably estimate the robot’s pose to align partial models on the fly, and how to design the robot’s movement patterns in large environment to effectively reduce error accumulation and to increase building efficiency. To address these two issues in this work, we propose an algorithm to adaptively fuse the IMU information with the visual tracking for the first issue, and design two robot movement patterns for the second issue. The preliminary experiments on a TurtleBot2 robot platform show that our RGB-D SLAM system works well even for difficult situations such as weaktextured space, or presence of pedestrians. |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/20948]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_机器人视觉团队 |
| 作者单位 | 1.中国科学院自动化所 2.中国科学院大学 |
| 推荐引用方式 GB/T 7714 | Meng XR,Gao W,Hu ZY. Robust 3D Indoor Map Building via RGB-D SLAM with Adaptive IMU Fusion on Robot[C]. 见:. 上海. 2017.9. |
入库方式： OAI收割
来源：自动化研究所
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