A real-time human-robot interaction system based on gestures for assistive scenarios
Cita com:
hdl:2117/95870
Tipus de documentArticle
Data publicació2016
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
:
Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
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.
CitacióCanal, G., Escalera, S., Angulo, C. A real-time human-robot interaction system based on gestures for assistive scenarios. "Computer vision and image understanding", 2016, vol. 149, p. 65-77.
ISSN1077-3142
Versió de l'editorhttp://www.sciencedirect.com/science/article/pii/S107731421600076X
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
1744-A-Real-tim ... or-assistive-scenarios.pdf | 1,463Mb | Visualitza/Obre |