A hybrid algorithm for tracking and following people using a robotic dog

The capability to follow a person in a domestic environment is an important prerequisite for a robot companion. In this paper, a tracking algorithm is presented that makes it possible to follow a person using a small robot. This algorithm can track a person while moving around, regardless of the sometimes erratic movements of the legged robot. Robust performance is obtained by fusion of two algorithms, one based on salient features and one on color histograms. Reinitializing object histograms enables the system to track a person even when the illumination in the environment changes. By being able to re-initialize the system on run time using background subtraction, the system gains an extra level of robustness.