GEOMETRICAL CALIBRATION FOR THE PANROVER: A STEREO OMNIDIRECTIONAL SYSTEM FOR PLANETARY ROVER - E. Simioni; C. Pernechele; C. Re; L. Lessio; G. Cremonese (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020)
A novel panoramic stereo imaging system is proposed in this paper. The system is able to carry out a 360° stereoscopic vision, useful for rover autonomous-driving, and capture simultaneously a high-resolution stereo scene. The core of the concept is a novel "bifocal panoramic lens" (BPL) based on hyper hemispheric model (Pernechele et al. 2016). This BPL is able to record a panoramic field of view (FoV) and, simultaneously, an area (belonging to the panoramic FoV) with a given degree of magnification by using a unique image sensor. This strategy makes possible to avoid rotational mechanisms. Using two BPLs settled in a vertical baseline (system called PANROVER) allows the monitoring of the surrounding environment in stereoscopic (3D) mode and, simultaneously, capturing an high-resolution stereoscopic images to analyse scientific cases, making it a new paradigm in the planetary rovers framework. Differently from the majority of the Mars systems which are based on rotational mechanisms for the acquisition of the panoramic images (mosaicked on ground), the PANROVER does not contain any moving components and can rescue a hi-rate stereo images of the context panorama. Scope of this work is the geometric calibration of the panoramic acquisition system by the omnidirectional calibration methods (Scaramuzza et al. 2006) based on Zhang calibration grid. The procedures are applied in order to obtain well rectified synchronized stereo images to be available for 3D reconstruction. We applied a Zhang chess boards based approach even during STC/SIMBIO-SYS stereo camera calibration (Simioni et al. 2014, 2017). In this case the target of the calibration will be the stereo heads (the BPLs) of the PANROVER with the scope of extracting the intrinsic parameters of the optical systems. Differently by previous pipelines, using the same data bench the estimate of the extrinsic parameters is performed.