Can stereo vision replace a Laser Rangefinder?

Many robotic systems combine cameras with Laser Rangefinders (LRF) for simultaneously achieving multi-purpose visual sensing and accurate depth recovery. Employing a single sensor modality for accomplishing both goals is an appealing proposition because it enables substantial savings in equipment, and tends to decrease the overall complexity of the system. This article explores the possibility of replacing LRF by passive stereo vision for reconstructing the scene along a 2D scan plane. We present a new stereo algorithm that is specifically tailored for the purpose. The algorithm recovers the depth along the scan plane using a symmetry-based matching cost (SymStereo), and refines the raw estimates by applying dynamic programming, followed by a Markov Random Field (MRF) that decides if the reconstructed contour is a line or not. We report for the first time comparative experiments between Stereo Rangefinding (SRF) and LRF. The results are encouraging by showing that SRF can be a plausible alternative to LRF in several application scenarios. Moreover, since SRF also enables independent depth estimates along multiple scan planes with arbitrary orientation, being the only constraint that the scan plane intersects the stereo baseline, it is an important benefit that can be decisive for many robotic applications.