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Integration of Camera and Inertial Measurement Unit for Entire Human Robot Interaction Using Machine Learning Algorithm

 
: Haghighi, Azam; Bdiwi, Mohamad; Putz, Matthias

:

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Instrumentation and Measurement Society:
16th IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2019 : March 21-24, 2019, Istanbul, Turkey
Piscataway, NJ: IEEE, 2019
ISBN: 978-1-7281-1820-8
ISBN: 978-1-7281-1819-2
ISBN: 978-1-7281-1821-5
S.741-746
International Multi-Conference on Systems, Signals and Devices (SSD) <16, 2019, Istanbul>
Englisch
Konferenzbeitrag
Fraunhofer IWU ()
camera; learning algorithm; machine learning; Man machine system

Abstract
Importance of robots in industrial applications is a well-known fact. There are many tasks in industries, which can't be done alone by a robot or alone by a worker. Therefore, there is a need to establish a reliable and safe interaction environment between robots and workers. To do so, some information about the worker should be conveyed to the robot. This article focuses on industrial Human-Robot Interaction. For a safe and efficient Human-Robot Interaction, a robot needs to know about worker's position, posture and gesture. This paper proposes integration of an Inertial Measurement Unit (IMU) and a 3D camera as an image sensor to eliminate each other drawbacks and applies machine learning algorithm to detect postures and gestures of worker. Some experimental results during the interaction with heavy-duty robot will be presented.

: http://publica.fraunhofer.de/dokumente/N-589150.html