Paper Info
Title
A real-time Human-Robot Interaction system based on gestures for assistive scenarios.
Abstract
We present a multi-robot human interaction system with two robots and a depth sensor.It includes a static and dynamic gestures recognition module.The set of gestures is described using arm/body and facial/head features.Interactive disambiguation for floor and object detection based on pointed location.Tested with several real users as well as with an offline test setting. Natural and intuitive human interaction with robotic systems is a key point to develop robots assisting people in an easy and effective way. In this paper, a Human Robot Interaction (HRI) system able to recognize gestures usually employed in human non-verbal communication is introduced, and an in-depth study of its usability is performed. The system deals with dynamic gestures such as waving or nodding which are recognized using a Dynamic Time Warping approach based on gesture specific features computed from depth maps. A static gesture consisting in pointing at an object is also recognized. The pointed location is then estimated in order to detect candidate objects the user may refer to. When the pointed object is unclear for the robot, a disambiguation procedure by means of either a verbal or gestural dialogue is performed. This skill would lead to the robot picking an object in behalf of the user, which could present difficulties to do it by itself. The overall system - which is composed by a NAO and Wifibot robots, a KinectTM v2 sensor and two laptops - is firstly evaluated in a structured lab setup. Then, a broad set of user tests has been completed, which allows to assess correct performance in terms of recognition rates, easiness of use and response times.
Year
DOI
Venue
2016
10.1016/j.cviu.2016.03.004
Computer Vision and Image Understanding
Keywords
Field
DocType
Gesture recognition,Human Robot Interaction,Dynamic Time Warping,Pointing location estimation
Object detection,Computer vision,Dynamic time warping,Gesture,Usability,Gesture recognition,Human interaction,Artificial intelligence,Robot,Human–robot interaction,Mathematics
Journal
Volume
Issue
ISSN
149
C
1077-3142
Citations 
PageRank 
References 
14
0.63
26
Authors
3
Name
Order
Citations
PageRank
Gerard Canal1283.76
Sergio Escalera21415113.31
Cecilio Angulo343457.48