eBear: An Expressive Bear-Like Robot
This work addresses human-robot interaction for applications in social robotics, but it is incremental as it builds on existing methods for facial expression synthesis and recognition.
The researchers developed an expressive bear-like robot, eBear, with a hybrid mechanical and LCD-display face to explore human-robot interaction through verbal and non-verbal communication, and user acceptance investigations evaluated its likability.
This paper presents an anthropomorphic robotic bear for the exploration of human-robot interaction including verbal and non-verbal communications. This robot is implemented with a hybrid face composed of a mechanical faceplate with 10 DOFs and an LCD-display-equipped mouth. The facial emotions of the bear are designed based on the description of the Facial Action Coding System as well as some animal-like gestures described by Darwin. The mouth movements are realized by synthesizing emotions with speech. User acceptance investigations have been conducted to evaluate the likability of these facial behaviors exhibited by the eBear. Multiple Kernel Learning is proposed to fuse different features for recognizing user's facial expressions. Our experimental results show that the developed Bear-Like robot can perceive basic facial expressions and provide emotive conveyance towards human beings.