Maze Navigation Using Optical Flow

Abstract

Some recent work with autonomous robots has focused on using optical flow for "direct" control of speed and rotation in obstacle avoidance and other simple behaviors. This work has been inspired by work with insects showing similar mechanisms. To extend these behaviors, three methods of maze navigation are investigated in a simulated robot modeled after a real one. A motor-based method places biases in the obstacle avoidance control law used previously. A perception-based method uses optical flow to detect possibilities for action (e.g., to turn left or right). Both of these require that the agent have a list of biases in order to navigate. The third method, called the Salience Centroid Method, is based on a theory of the role of the hippocampus in rat navigation. This method trades off the memory of the first two for more advanced perceptual processing and allows the most flexible behavior. 1 Introduction In the last few years, a number of researchers have explored the use of optica...