Vision-based docking system for an aromatic-hydrocarbon-inspired reconfigurable robot

Aromatic hydrocarbons generally refer to compounds containing benzene rings. Many types of isomers can be formed by replacing hydrogen atoms on the benzene ring. In this paper, an aromatic-hydrocarbon-inspired modular robot (AHIMR) is proposed. The robot can be reassembled into different configurations suitable for various task requirements. A vision-based docking system is designed for the AHIMR. The system primarily consists of two stages: a remote guidance stage and a precise docking stage. During the remote guidance stage, an object module is identified using an illumination adaptive target recognition algorithm, and then the active module moves to the docking area through communication with ZigBee. In the precise docking stage, the active module calculates the relative pose with the object module using a perspective-n-point method and dynamically adjusts its posture to dock. In this process, a Kalman filter is used to reduce target occlusion and jitter interference. In addition, the docking system feasibility is verified via several simulation experiments. The module docking accuracy is controlled within 0.01 m, which meets the reconfiguration task requirements of the AHIMR. In the AHIMR submodule docking experiment, the active module accurately moves to the expected position with a docking success rate of 95%.