Robust 3D Indoor Map Building via RGB-D SLAM with Adaptive IMU Fusion on Robot

	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	多模态人工智能系统全国重点实验室_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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