A Survey on Visual Simultaneously Localization and Mapping
Zijie Zhang, Jing Zeng
- 发表年份
- 2022
- 引用次数
- 2
- 访问权限
- 开放获取
摘要
Visual simultaneous localization and mapping (VSLAM) is an important branch of intelligent robot technology, which refers to the use of cameras as the only external sensors to achieve self-localization in unfamiliar environments while creating environmental maps. The map constructed by slam is the basis for subsequent robots to achieve autonomous positioning, path planning and obstacle avoidance tasks. This paper introduces the development of visual Slam at home and abroad, the basic methods of visual slam, and the key problems in visual slam, and discusses the main development trends and research hotspots of visual slam.
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