DynamicFilter: an Online Dynamic Objects Removal Framework for Highly Dynamic Environments скачать в хорошем качестве

DynamicFilter: an Online Dynamic Objects Removal Framework for Highly Dynamic Environments

Authors: Tingxiang Fan*, Bowen Shen*, Hua Chen, Wei Zhang, and Jia Pan Project website: https://sites.google.com/view/dynamic... Abstract: The emergence of massive dynamic objects will diversify the spatial structure when robot navigates in urban environments. Therefore, the online removal of dynamic objects is critical. In this paper, we introduce a novel online removal framework for highly dynamic urban environments. The framework consists of the scan-to-map front-end and the map-to-map back-end modules. Both the front- and back-ends deeply integrate the visibility-based approach and map-based approach. The experiments validate the framework in highly dynamic simulation scenarios and real-world dataset. Video organized as follows: 0:05 simulation experiments 0:59 simulation results 1:10 real-world experiments in a shopping mall 2:54 results of the shopping mall 3:06 real-world experiments in an outdoor pedestrian zone 6:59 results of the outdoor pedestrian zone