Design of conversational humanoid robot based on hardware independent gesture generation
This work addresses the need for more natural human-robot interaction in care and support settings, such as for elderly and disability care, by improving gesture capabilities, though it appears incremental as it builds on existing labanotation systems.
The paper tackles the problem of generating realistic physical gestures for humanoid robots to enhance conversational interactions, proposing a hardware-independent method using labanotation to enable gesture generation across different robot platforms.
With an increasing need for elderly and disability care, there is an increasing opportunity for intelligent and mobile devices such as robots to provide care and support solutions. In order to naturally assist and interact with humans, a robot must possess effective conversational capabilities. Gestures accompanying spoken sentences are an important factor in human-to-human conversational communication. Humanoid robots must also use gestures if they are to be capable of the rich interactions implied and afforded by their humanlike appearance. However, present systems for gesture generation do not dynamically provide realistic physical gestures that are naturally understood by humans. A method for humanoid robots to generate gestures along with spoken sentences is proposed herein. We emphasize that our gesture-generating architecture can be applied to any type of humanoid robot through the use of labanotation, which is an existing system for notating human dance movements. Labanotation's gesture symbols can computationally transformed to be compatible across a range of robots with doddering physical characteristics. This paper describes a solution as an integrated system for conversational robots whose speech and gestures can supplement each other in human-robot interaction.