Visual-Pressure Fusion for Underwater Robot Localization With Online Initialization
Chao Hu, Shiqiang Zhu, Yiming Liang, Zonghao Mu, Wei Song
- 发表年份
- 2021
- 引用次数
- 23
摘要
The motion of underwater robot is usually slow, which leads to large scale error easily introduced in the positioning method based on monocular Visual Inertial Odometry (VIO). To solve the above problem, we present a positioning method based on visual-pressure fusion in this letter. Firstly, it is proved by observability analysis that when the robot's motion is not on the same horizontal plane, the system scale can be uniquely determined by monocular image and depth information; secondly, a novel visual-pressure initialization method is proposed, which can calculate the system scale and initial attitude with respect to world frame online; finally, we integrate our method into current advanced monocular Simultaneous Localization And Mapping (SLAM) system, and the effectiveness and superiority of the method are verified by experiments on simulation datasets and real datasets.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002