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Mobile robot simultaneous localization and mapping in dynamic environments
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DOI：10.1007/s10514-005-0606-4.png)
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We propose an on-line algorithm for simultaneous localization and mapping of dynamic environments. Our algorithm is capable of differentiating static and dynamic parts of the environment and representing them appropriately on the map. Our approach is based on maintaining two occupancy grids. One grid models the static parts of the environment, and the other models the dynamic parts of the environment. The union of the two grid maps provides a complete description of the environment over time. We also maintain a third map containing information about static landmarks detected in the environment. These landmarks provide the robot with localization. Results in simulation and real robots experiments show the efficiency of our approach and also show how the differentiation of dynamic and static entities in the environment and SLAM can be mutually beneficial.
Keyword:
mapping
occupancy grids
dynamic environments
SLAM
期刊
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4.3
论文数:
1.7K
被引数:
5.0K
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A probabilistic approach to concurrent mapping and localization for mobile robots.png)
MACHINE LEARNING
MACHINE LEARNINGIF2.9
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