To improve the autonomy of intelligent wheelchair/bed system (IWBS) docking, a visual measurement based framework for automatic docking is proposed. The docking process of IWBS is divided into remote guidance stage and shortrange visual docking stage. In the longrange guidance stage, a new artificial landmark on the wheelchair is collected and identified by the visual system on the ceiling. Afterwards, the artificial landmark is detected using a tracking method based on Kalman Filter (KF). The relative pose between the artificial landmark and the camera is then determined according to the P3P (perspectivethreepoint, P3P) visual positioning method. Using the transformation between the wheelchair coordinate system and the world coordinate of the remote guidance stage, the position and orientation of wheelchair are then determined. In shortrange docking stage, the guiding landmark of the docking target is collected using an onboard monocular vision system. The feature of the guiding landmark is used to estimate the relative pose between the wheelchair and the bed. Finally, the automatic docking of IWBS is realized according to the visual feedback in realtime. Numerous experiments are carried and experimental results show that the visual docking methods proposed in this work is feasible and effective.