The memory game: Creating a human-robot interactive scenario for ASIMO

Abstract

We present a human-robot interactive scenario consisting of a memory card game between Honda's humanoid robot ASIMO and a human player. The game features perception exclusively through ASIMO's on-board cameras and both reactive and proactive behaviors specific to different situational contexts in the memory game. ASIMO is able to build a dynamic environmental map of relevant objects in the game such as the table and card layout as well as understand activities from the player such as pointing at cards, flipping cards and removing them from the table. Our system architecture, called the Cognitive Map, treats the memory game as a multi-agent system, with modules acting independently and communicating with each other via messages through a shared blackboard system. The game behavior module can model game state and contextual information to make decisions based on different pattern recognition modules. Behavior is then sent through high-level command interfaces to be resolved into actual physical actions by the robot via a multi-modal communication module. The experience gained in modeling this interactive scenario will allow us to reuse the architecture to create new scenarios and explore new research directions in learning how to respond to new interactive situations.

Multicore and FPGA implementations of emotional-based agent architectures

“…The cores share a memory structure called blackboard [23]. Through this memory the processes read and write the important data as the appraisals, emotional states and motivations.…”