Robot navigation using an anthropomorphic visual sensor

The use of an anthropomorphic, retinalike visual sensor for navigation tasks is investigated. The main advantage, besides the topological scaling and rotation invariance, stems from the considerable data reduction obtained with nonuniform sampling, in conjunction with high resolution in the part of the field of view corresponding to the focus of attention. Active movements are also considered to be a beneficial feature, solving the depth-from-motion problem and maintaining a 3-D representation of the viewed scene. For short range navigation, a tracking egomotion strategy is adopted which greatly simplifies the motion equations and complements the characteristics of the retinal sensor. An algorithm for the computation of depth from motion is developed for image sequences acquired with the retinal sensor, and an error analysis is carried out to determine the uncertainty of range measurements. An experiment is presented in which depth maps are computed from a sequence of images sampled with the retinalike sensor, building a volumetric representation of the scene