Comparison of methods to efficient graph SLAM under general optimization framework
文献类型：会议论文
| 作者 | Haoran Li1,2 ; Qichao Zhang1,2; Dongbin Zhao1,2
|
| 出版日期 | 2017 |
| 关键词 | Optimization Slam Pose Graph |
| 期号 | * |
| 页码 | * |
| 英文摘要 | Simultaneous Localization and Mapping(SLAM) algorithms can infer the robot's trajectory as well as the map under unknown environment. Robust and time-efficient optimization methods are important requirements for SLAM. There are many algorithms designed for the graph optimization. However, it is hard to select an appropriate algorithm and corresponding software library, due to the difficulty of evaluating algorithms' adaptabilities under various situations. In this paper, we summarize these algorithms under general optimization framework, conduct several sets of experiments to compare these algorithms in three software libraries, and give some suggestions to choose algorithms. |
| 会议录 | YAC 2017
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19422]  |
| 专题 | 复杂系统管理与控制国家重点实验室_深度强化学习 |
| 作者单位 | 1.The state Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China 2.University of Chinese Academy of Sciences, Beijing, 100049, China |
| 推荐引用方式 GB/T 7714 | Haoran Li,Qichao Zhang,Dongbin Zhao. Comparison of methods to efficient graph SLAM under general optimization framework[C]. 见:. |
入库方式： OAI收割
来源：自动化研究所
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