Knowledge-sharing techniques for Egocentric Navigation

Abstract

Teams of humans and robots working together can provide effective solutions to problems. In such applications, effective human-robot teaming relies on being able to communicate information about the current perception or understanding of the environment. In this paper, human-robot teaming on navigational tasks is discussed. The role of the human user will be to specify the goal point(s) for the robot, and also to interact with the robot in the event of perceptual errors. A novel navigation method, Egocentric Navigation (ENav), has been developed based on egocentric representations. In this paper, two knowledge sharing methods are described which exploit the characteristics of ENav. In the first method, robots share Landmark EgoSpheres, and in the second method the robot shares it Sensory EgoSphere with the human user for visual perception correction.