From Points to Planes - Adding Planar Constraints to Monocular SLAM Factor Graphs
Charlotte Arndt, Reza Sabzevari, Javier Civera
Abstract
Planar structures are common in man-made environments. Their addition to monocular SLAM algorithms is of relevance in order to achieve more complete and higher- level scene representations. Also, the additional constraints they introduce might reduce the estimation errors in certain situations. In this paper we present a novel formulation to incorporate plane landmarks and planar constraints to feature- based monocular SLAM. Specifically, we enforce in-plane points to lie exactly in the plane they belong to, propagating such information to the rest of the states. Our formulation, differently from the state of the art, allows us to incorporate general planes, independently of depth information or CNN segmentation being available (although we could also use them). We evaluate our method in several sequences of public databases, showing accurate plane estimations and pose accuracy on par with state- of-the-art point-only monocular SLAM.