Real-Time Marker-Based Monocular Autonomous Docking in Semi-Unstructured Indoor Environments.

Environmental changes can severely disrupt the docking sections of transportation systems in factories. Such disruptions not only halt the production line but also necessitate human intervention for loading and unloading, posing safety risks. To address this, we introduce an autonomous docking system designed for resilience in semi-unstructured environments, especially when faced with varying light conditions and physical alterations. Our solution involves an advanced ArUco marker system. By integrating the yaw orientation of the marker with angular velocity data from an inertial measurement unit, we achieve a homogeneous matrix reconstruction. This enhanced marker data then guides a reference trajectory for docking, controlled by a PI Pure Pursuit mechanism. To further improve marker recognition, we have incorporated reflective and anti-reflective materials and modulated the marker's white margin. Our test results indicate a significant improvement in the detection range of a 21cm marker expanded from 60cm to 2m. Moreover, our system ensures a docking precision of $\pm 31\text{mm}$ and $\pm 1.82^{\circ}$ .