Rotatable Lens‐Based 3D Reconstruction Method for Monocular Vision Systems

ABSTRACT Vision‐based three‐dimensional (3D) reconstruction plays an important role in robotic grasping and manipulation by providing accurate 3D information for target localization and motion planning. These tasks are usually performed in confined environments, where the vision‐based measurement systems are required to provide higher measurement accuracy while occupying a smaller volume. However, traditional stereo vision systems struggle to simultaneously achieve high precision and small volume, which limits their deployment in confined environments. In this paper, we developed a rotatable‐lens monocular vision system (RLMVS) consisting of a monocular camera, a wedge‐shaped lens, and an automatic rotation mechanism for the wedge‐shaped lens. A flexible learning‐based calibration method was proposed for the RLMVS. Furthermore, we proposed a rotatable lens‐based 3D reconstruction (RLR) method for RLMVS, which is the first time using the refraction of the light induced by a rotating wedge‐shaped lens to enable 3D reconstruction. Experimental results demonstrated that, compared with the traditional stereo vision system, the RLMVS reduced the RM measurement error by 61.2%, and reduced the overall volume of the 3D sensing modules by 46.5%. These advantages make the RLMVS particularly suitable for robotic manipulation in confined environments. We integrated the RLMVS with a robotic arm and performed grasping of small objects in a confined environment, demonstrating that the RLMVS provided a compact, low‐cost, yet accurate 3D sensing modality for robotic manipulation in confined environments.