Improving Robotic Bin-Picking Performances through Human–Robot Collaboration

Abstract

The automation of bin-picking processes has been a research topic for almost two decades. General-purpose equipment, however, still does not show adequate success rates to find application in most industrial tasks. Human–robot collaboration in bin–picking tasks can increase the success rate by exploiting human perception and handling skills and the robot ability to perform repetitive tasks. The aim of this paper, starting from a general-purpose industrial bin picking equipment comprising a 3D–structured light vision system and a collaborative robot, consists in enhancing its performance and possible applications through human–robot collaboration. To achieve successful and fluent human–robot collaboration, the robotic workcell must meet some hardware and software requirements that are defined below. The proposed strategy is tested in some sample tests: the results of the experimental tests show that collaborative functions can be particularly useful to overcome typical bin picking failures and to improve the fault tolerance of the system, increasing its flexibility and reducing downtimes.