NDLI: Human Body Pose Interpretation and Classification for Social Human-Robot Interaction

Content Provider	Springer Nature Link
Author	McColl, Derek Zhang, Zhe Nejat, Goldie
Copyright Year	2011
Abstract	A novel breed of robots known as socially assistive robots is emerging. These robots are capable of providing assistance to individuals through social and cognitive interaction. However, there are a number of research issues that need to be addressed in order to design such robots. In this paper, we address one main challenge in the development of intelligent socially assistive robots: The robot’s ability to identify human non-verbal communication during assistive interactions. In particular, we present a unique non-contact and non-restricting automated sensor-based approach for identification and categorization of human upper body language in determining how accessible a person is to the robot during natural real-time human-robot interaction (HRI). This classification will allow a robot to effectively determine its own reactive task-driven behavior during assistive interactions. Human body language is an important aspect of communicative nonverbal behavior. Body pose and position can play a vital role in conveying human intent, moods, attitudes and affect. Preliminary experiments show the potential of integrating the proposed body language recognition and classification technique into socially assistive robotic systems partaking in HRI scenarios.
Starting Page	313
Ending Page	332
Page Count	20
File Format	PDF
ISSN	18754791
Journal	International Journal of Social Robotics
Volume Number	3
Issue Number	3
e-ISSN	18754805
Language	English
Publisher	Springer Netherlands
Publisher Date	2011-06-04
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Socially assistive robots Non-verbal communication 3D human body pose detection and classification Human-robot interaction Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Philosophy Control and Systems Engineering Social Psychology Electrical and Electronic Engineering Human-Computer Interaction

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