| Intelligent robots are a kind of robots that are able to work in complex environments with the capacities of self-organizing and self-planning. Navigation problem is a hot issue concerned in researching on such kind of robots. Its aim is to move purposely and do the job without aids. With supports of the project of National Natural Science Foundation of China and the project of Excellent Youth Fund in Hubei province, this paper aims to develop a new algorithm for navigating based on the Simultaneous Localization and Mapping (SLAM) algorithm to make the robots totally autonomous in the unknown but structured environments.The navigation techniques are firstly reviewed in this paper and then the Simultaneous Localization and Mapping (SLAM) problem is introduced, based on the analysis of the localization problem and the map building problem which are two key points in the navigation techniques, including its structure, characteristics, categories and so on. As there is a conflict between the requirements of computational complexity and information-richness within the point-feature based SLAM algorithm, a line-feature based SLAM algorithm is well presented in this paper. All operations required for building and maintaining this map, such as model-setting, data association, and state-updating are described and formulated. This approach has been programmed and successfully tested in the simulation workTo meet the need of path planning in navigation, here we mainly concern the local planning, that is, obstacle avoiding. We introduce the VFH/VFH+, an algorithm for obstacle avoidance, in detail in the paper. What is more, in our work, we combine VFH+ and SLAM together to develop a new way for navigation, which has more applications and behaves better than the one based merely on VFH+ does. |
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