Multi-camera Fruit Localization in Robotic Harvesting

Motivated by an effort to study layered vision systems for robotic harvesting, this paper investigates the problem of fruit localization using multiple cameras in the fruit detection layer of the vision system. A pseudo stereo-vision approach is presented where fruit matching is accomplished by loosely holding the epipolar constraint to reduce computation time. In the presence of noise, heuristics are presented to identify the greatest subset of cameras with matched fruits. Subsequently, the fruit depth is obtained by minimizing the summation of the image reprojection error in cameras with matching fruit. Monte Carlo simulations are performed to establish localization efficiency of the proposed approach under varying design parameters and image noise.