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For exploring the interior unknown environment, by using an autonomous mobile robot this paper proposes a high-effect autonomous environment exploration algorithm based on a hybrid topological-metric map. The topological map based on environment Opening-Points is built in real-time according to current sensor information. The optimal instant target is selected as the exploration direction for the next step by analyzing and dealing with the Opening-Points. In the framework of Rao-Blackwellized particle filter (RBPF), the grid map based Simultaneous Localization and Mapping (SLAM) is introduced into the autonomous exploration process of the mobile robot, which provides the accurate position estimate to improve the position accuracy of the topological node effectively and complete the exploration task smoothly. The exploration algorithm based on the above two strategies gives consideration to both accuracy and efficiency. The validity and practicability of the proposed exploration approach was validated by a lot of experiments on the mobile robot Pioneer3-DX.
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