Cognitive Tools for Humanoid Robots in Space

摘要

The effective use of humanoid robots in space will depend upon the efficacy of interaction between humans and robots. The key to achieving this interaction is to provide the robot with sufficient skills for natural communication with humans so that humans can interact with the robot almost as though it were another human. This paper describes the design, implementation, and capabilities of a robotic system architecture for a robot which can be used (at some level) to collaborate with a human. The capabilities required of the robot include voice recognition, natural language understanding, gesture recognition, spatial reasoning, and cognitive modeling with perspective-taking. These represent a small subset of potential capabilities humans utilize with one another in collaborating to perform a task in a complex environment, and barely scratches the surface of capabilities that one might want to build into an intelligent, collaborative robot. The capabilities described here have been successfully implemented and demonstrated on several mobile robotic platforms (Sofge, et al., 2004), and the authors are now porting them to Robonaut. They also are extending the capabilities of the cognitive architectures (both ACT- R/S and Polyscheme) and their perspective-taking cognitive models. Future work will focus on enhancing the cognitive models through expanded rule sets and cognitively plausible behaviors and reasoning mechanisms, and adding learning capabilities to the models so that the robots may be able to acquire new knowledge and skills through interaction with humans and while performing tasks.