Article

Visual-Inertial-Encoder RGB-D SLAM for Differential Wheeled Robots

The study proposes a generative measurement model for encoders and derives the maximum a posteriori estimation expression and the Jacobians required for optimization, building a tightly coupled visual-inertial-encoder RGB-D SLAM system. On a self-built dataset, the system's real-time state estimation achieves a root mean square error of about 2-7 cm, used to compensate for the failure of pure vision solutions during temporary feature point loss and fast motion. The source code and the dataset containing encoder information have been made public.

Part of the event: Vision-Inertial-Encoder RGB-D SLAM System Proposed

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