Incremental sparse GP regression for continuous-time trajectory estimation and mapping

详细信息    查看全文

• 作者：Xinyan Yan^a ; ^{xinyan.yan@cc.gatech.edu}Author Vitae ; Vadim Indelman^bAuthor Vitae ; Byron Boots^aAuthor Vitae
• 关键词：State estimation ; Localization ; Continuous time ; SLAM ; Gaussian process regression
• 刊名：Robotics and Autonomous Systems
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：87
• 期：Complete
• 页码：120-132
• 全文大小：2236 K
• 卷排序：87

文摘

An incremental sparse GP regression algorithm for STEAM problems is proposed. The benefits of GP-based approaches and incremental smoothing are combined. The approach elegantly handles asynchronous and sparse measurements. Results indicate significant speed-up in performance with little loss in accuracy.