Coaching Robots to Play Soccer via Spoken-Language

The objective of this paper and our current research is to develop a human-robot interaction architecture that will let human coaches train robots to play soccer via spoken language. This work exploits recent developments in cognitive science, particularly notions of grammatical constructions as formmeaning mappings in language, and notions of shared intentions as distributed plans for interaction and collaboration between humans and robots linking perceptions to action responses. We define two sets of voice-driven commands for human-robot interaction. The first set involves action commands requiring robots to perform certain behaviors, while the second set involves interrogation commands requiring a response from the robot. We then define two training levels to teach robots new forms of soccer-related behaviors. The first level involves teaching new basic behaviors based on action and interrogation commands. The second level involves training new complex behaviors based on previously learnt behaviors. We explore the two coaching approaches using Sony AIBO robot s in the context of RoboCup soccer standard platform league previously known as the four-legged league. We describe the coaching process, experiments, and results. We also discuss the state of advancement of this work.