Multicamera Visual SLAM For Vineyard Inspection

Christos Kokas, Athanasios Mastrogeorgiou, Konstaninos Machairas,
Konstantinos Koutsoukis, Student members, IEEE, and Evangelos Papadopoulos, Life Fellow, IEEE
The authors are with the Control Systems Lab (CSL), School of Mechanical Engineering, National Technical University of Athens
Automating the process of collecting samples (e.g., images) from a vineyard can help monitor the grapes' condition with precision and prevent the spreading of diseases. A critical part of this task is the development of a robust localization algorithm so that (a) a robot is able to carry out the inspection process and (b) the vine-grower knows exactly which part of the vineyard has been inspected. In this paper, we propose a novel approach for enhancing the robustness of vSLAM by utilizing multiple stereo cameras and a novel method for detecting loops in homogeneous environments based on AprilTags, where state-of-the-art approaches may find it difficult to detect them. We test the accuracy of our method using a wheeled Robotic Platform (RP) in simulation and in a synthetic vineyard developed at CSL, NTUA \cite{csl_ntua}. The developed method achieves high accuracy in the localization of the RP in the vineyard and robustness even when a featureless object covers a large part of the Field of View of one camera. The developed software is available for testing at the CSL's bitbucket repository, i.e.:
bitbucket.org/...