Ran Zhao and Daniel Sidobre
Collaborative manufacturing, industrial robotics, human–robot interaction
This paper proposes a sensor-based and on-line trajectory generation (OTG)-based framework for the human–robot interaction in collaborative manufacturing environments. A vision system is used to enforce safety by detecting the human position in real time. To guarantee safety while maintaining the maximum level of productivity, this paper introduces a safety system to optimize the robot velocity. In addition, visual gesture reorganization is applied for controlling an industrial robot. A predefined set of gestures is employed to trigger various robot tasks. An OTG algorithm enables real-time trajectory generation hence fast reaction to human activities. Consequently, robots can coexist and cooperate with the human in a shared workspace. A preliminary experiment was carried out on a KUKA industrial robot to verify the effectiveness of the proposed method.
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