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摘要: 该文研究移动机器人自主创建地图中的不确定传感信息处理问题,基于灰色系统理论 提出了一种新的对传感信息进行解释和融合的方法用于声纳信息的处理,并以此建立环境的栅 格地图.声纳的传感信息存在较大的不确定性,这里引入灰数的概念来表示和处理这种不确定 性,对于机器人在不同位置的测量结果,根据灰色系统理论对信息的理解方式设计融合方法,得 到一个对环境的整体表示.通过仿真环境和真实机器人平台上进行的创建地图实验,表明这种 方法具有良好的鲁棒性和准确度.Abstract: Autonomous map building of mobile robots is a fundamental task in robotics research. This paper focuses on the problem of uncertainty sensor information processing in map building. In order to process sonar information and build grid-based map of environment, a new method based on grey system theory Is proposed which interprets and combines sensor information. We introduce the concept of "Grey Number" to model and handle the uncertainty of sonar sensing information. Furthermore, a novel fusion method is proposed, which refers to the paraphrase of information by grey system theory. Map building experiments are performed both on simulation platforms and real mobile robots. Experiment results show that our method is robust and accurate.
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Key words:
- Mobile robot /
- map building /
- uncertainty information /
- grey system theory /
- grid map
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