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- W2910390815 abstract "Optical images provide rich features but require extensive computation resources to process for SLAM. When there are limited computation resources on the robots, it becomes a heavy burden to process the images in real-time. This paper presents the design and implementation of key-frame selection algorithm for multiple robots simultaneous localization and tracking on the multi-robot soccer games which have pre-defined field and objects. Compared to traditional key-frame selection algorithms, this work makes use of the temporal and spatial relationship among objects on the pre-defined field to compute the information entropy. The selection ratio can be adjusted by two parameters: entropy threshold and the maximum moving distance. The experimental results show that the developed method can effectively detect the change of scene using selected key-frames. And comparing with the localization results using all the images, using less than 20% of all images after walking 11,203mm it only increase up to 0.87% trajectory errors." @default.
- W2910390815 created "2019-01-25" @default.
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- W2910390815 date "2018-10-01" @default.
- W2910390815 modified "2023-09-25" @default.
- W2910390815 title "Key-frame Selection for Multi-robot Simultaneous Localization and Tracking in Robot Soccer Field" @default.
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- W2910390815 doi "https://doi.org/10.1109/iros.2018.8593785" @default.
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