Imaging rover technology: characteristics, possibilities and possible improvements

Valerio Baiocchi, Chiara Piccaro, Massimo Allegra, Valeria Giammarresi, Felicia Vatore
2018 Journal of Physics, Conference Series  
The terrestrial photogrammetric survey allows to acquire geometric characteristics of objects quickly and with handy and inexpensive hardware. Traditionally, these measurements require some hours of time between the choice of the acquisition points, the setting up of the camera, the survey of the topographic support network and subsequent processing of the acquired data. The upcoming of advanced algorithms such as "structure from motion" (SFM) [1] and the recent availability of optical cameras
more » ... of optical cameras with increasing resolution combined with increasing resources of mass storage [1], make it possible to create dedicated hardware with potentials not possible with these technologies so far. Of particular interest in this field is the coming of so-called "imaging rovers", i.e. cameras that allow simultaneous acquisition of multiple images, covering a 360-degree panorama and in some cases, directly positioned thanks to GPS/GNSS differential receivers with centimeter accuracy. The recent availability of these innovative techniques requires careful verification to assess their capabilities, accuracy, precision and possible limitations. This work presents the first systematic verification of one of these latest generation devices in different conditions and for different applications. It has been verified that in many cases it is possible to obtain threedimensional surveys quickly with information contents comparable to those of more expensive and less handy instruments such as terrestrial laser scanning. The development of these techniques could lead to operational simplifications and greater efficiency also in complementarity with the reliefs from UAVs that, as it's well known, show some limitations in the so-called urban canyons.
doi:10.1088/1742-6596/1110/1/012008 fatcat:xotg53fevncirid3tj5qewv2u4