Hybrid metric-topological-semantic mapping in dynamic environments

Romain Drouilly, Patrick Rives, Benoit Morisset
2015 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)  
Mapping evolving environments requires an update mechanism to efficiently deal with dynamic objects. In this context, we propose a new approach to update maps pertaining to large-scale dynamic environments with semantics. While previous works mainly rely on large amount of observations, the proposed framework is able to build a stable representation with only two observations of the environment. To do this, scene understanding is used to detect dynamic objects and to recover the labels of the
more » ... cluded parts of the scene through an inference process which takes into account both spatial context and a class occlusion model. Our method was evaluated on a database acquired at two different times with an interval of three years in a large dynamic outdoor environment. The results point out the ability to retrieve the hidden classes with a precision score of 0.98. The performances in term of localisation are also improved.
doi:10.1109/iros.2015.7354096 dblp:conf/iros/DrouillyRM15 fatcat:c5vmzxsdtbc2dibvvli4kyd25u