<title>Adaptive control of camera position for stereo vision</title>

Abstract

A major problem in using two-camera stereo machine vision to perform real-world tasks, such as visual object tracking, is deciding where to position the cameras. Humans accomplish the analogous task by positioning their heads and eyes for optimal stereo effects. This paper describes recent work toward developing automated control strategies for camera motion in stereo machine vision systems for mobile robot navigation. Our goal is to achieve fast, reliable pursuit of a target while avoiding obstacles. Our strategy results in smooth, stable camera motion despite robot and target motion. Our algorithm has been shown to be successful at navigating a mobile robot, mediating visual target tracking and ultrasonic obstacle detection. The architecture, hardware, and simulation results are discussed.