Design of Single-Camera Mirrored Binocular Vision Sensor With Single-Plane Mirror

Environmental perception, which is crucial for robotic decision-making and execution control, presents significant challenges in developing lightweight compact, low-cost, real-time, and flexible 3-D vision sensor with moderate measurement accuracy. Compared with stereo-vision sensor based on multicamera, single-camera mirrored binocular sensor provides more compact structure and lower cost. Furthermore, the single-camera mirrored binocular has the advantage of real-time measurement compared with the actual binocular realized by moving camera. This article develops a mirrored binocular vision sensor with single-plane mirror and only one camera. A single-plane mirror is used to form a virtual binocular, and the structural parameters of the sensor are optimized from the aspects of spatial arrangement, field of view (FOV), measurement accuracy, and depth of field (DOF). Based on a planar target calibration approach, the camera calibration accuracy is 0.064 pixels, and the average calibration error of the sensor is 0.022 mm. Using deep learning algorithm, the operational performance in both structured and unstructured environments is validated through experiments, and the results demonstrate that the accuracy of 3-D reconstruction is greater than 0.1 mm.