Authors:
David Bricher
and
Andreas Müller
Affiliation:
Institute of Robotics, Johannes Kepler University, Altenbergerstraße 69, 4040 Linz, Austria
Keyword(s):
Human-robot-collaboration, Latency Determination, ISO/TS 15066, Deep Learning, Human Recognition, Body Part Recognition, HRC Safety Standard.
Abstract:
Today, an efficient and flexible usage of lightweight robots in collaborative working spaces is strongly limited by the biomechanical safety regulations of ISO/TS 15066. In order to maximize the robot performance without contradicting the technical standards and recommendations, a safety framework is introduced, which makes use of state-of-the-art deep learning algorithms for human recognition and human body part identification. Particularly, a generic vision-based method for the determination of the occurring latencies is proposed. To this end, the different latency contributions from the recognition process up to the process of adapting the robot speed to an ISO-conform level are analyzed in detail.