VINet: Visual and Inertial-based Terrain Classification and Adaptive Navigation over Unknown Terrain

09/16/2022

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by   Tianrui Guan, et al.

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We present a visual and inertial-based terrain classification network (VINet) for robotic navigation over different traversable surfaces. We use a novel navigation-based labeling scheme for terrain classification and generalization on unknown surfaces. Our proposed perception method and adaptive control framework can make predictions according to terrain navigation properties and lead to better performance on both terrain classification and navigation control on known and unknown surfaces. Our VINet can achieve 98.37 accuracy under supervised setting on known terrains and improve the accuracy by 8.51 mobile tracked robot for trajectory following and navigation on different terrains, and we demonstrate an improvement of 10.3 controller in terms of RMSE.