Biologically-inspired visual landmark learning and navigation for mobile robots

Presents a biologically-inspired method for navigating using visual landmarks which have been self-selected within natural environments. A landmark is a region of the grabbed image which is chosen according to its reliability measured through a phase (turn back and look) that mimics the behavior of some social insects. From the self-chosen landmarks suitable navigation information can be extracted following a well known model introduced in biology to explain the bee´s navigation behavior. The landmark selection phase affects the conservativeness of the navigation vector field thus allowing us to explain the navigation model in terms of a visual potential function which drives the navigation to the goal. The experiments have been performed using a Nomad200 mobile robot equipped with monocular color vision