Natural human-robot interaction through spatial language: A Dynamic Neural Field approach

For an autonomous robotic system, the ability to share the same workspace and interact with humans is the basis for cooperative behavior. In this work, we investigate human spatial language as the communicative channel between the robot and the human, facilitating their joint work on a tabletop. We specifically combine the theory of Dynamic Neural Fields that represent perceptual and cognitive states with motor control and linguistic input in a robotic demonstration. We show that such a neural dynamic framework can integrate across symbolic, perceptual, and motor processes to generate task-specific spatial communication in real time.