Optimization and Rapid Prototyping of Catadioptric Omnidirectional Stereo Sensors

Omnidirectional stereo imaging provides useful depth information for autonomous navigation. In principle, omnidirectional stereo images can be achieved at a low cost, using a single camera and two curved mirrors, but such systems are not widely deployed. Here we describe the optimization and rapid prototyping of a low-cost omnidirectional stereo sensor for a telepresence robot. We consider single-viewpoint and non-single-viewpoint designs. We present a new way of relaxing single-viewpoint constraints, while retaining the ability to vertically rectify images. We also present a method of optimizing the resulting design to minimize depth errors. However, we show that despite these steps, nonsingle-viewpoint designs produce stereo disparities over a more practical range of distances. The lack of a single viewpoint could potentially introduce distortions that affect stereo matching, but these distortions are removed by projecting rays through the mirror geometry. We also describe a new method for rapid prototyping of curved mirrors using 3D printing and vacuum forming.