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Robust 3D Indoor Map Building via RGB-D SLAM with Adaptive IMU Fusion on Robot
Meng XR(孟馨蕊)1,2; Gao W(高伟)1,2; Hu ZY(胡占义)1,2
2018
会议名称International Conference on Image and Graphics
页码454-465
会议日期2017.9
会议地点上海
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. 
关键词Camera Pose Estimation Rgb-d Slam Imu Robot Movement Pattern Calibration
收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/20948
专题模式识别国家重点实验室_机器人视觉
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],2018:454-465.
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