查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news reporting from Reggio Emilia, Italy, by NewsRx journal ists, research stated, "Collaborative robots (cobots) have seen widespread adopt ion in industrial applications over the last decade. Cobots can be placed outsid e protective cages and are generally regarded as much more intuitive and easy to program compared to larger classical industrial robots." The news correspondents obtained a quote from the research from the University o f Modena and Reggio Emilia, "However, despite the cobots' widespread adoption, t heir collaborative potential and opportunity to aid flexible production processe s seem hindered by a lack of training and understanding from shop floor workers. Researchers have focused on technical solutions, which allow novice robot users to more easily train collaborative robots. However, most of this work has yet t o leave research labs. Therefore, training methods are needed with the goal of t ransferring skills and knowledge to shop floor workers about how to program coll aborative robots. We identify general basic knowledge and skills that a novice m ust master to program a collaborative robot. We present how to structure and fac ilitate cobot training based on cognitive apprenticeship and test the training f ramework on a total of 20 participants using a UR10e and UR3e robot. We consider ed two conditions: adaptive and self-regulated training. We found that the facil itation was effective in transferring knowledge and skills to novices, however, found no conclusive difference between the adaptive or self-regulated approach. The results demonstrate that, thanks to the proposed training method, both group s are able to significantly reduce task time, achieving a reduction of 40% , while maintaining the same level of performance in terms of position error. No te to Practitioners-This paper was motivated by the fact that the adoption of sm aller, so-called collaborative robots is increasing within manufacturing but the potential for a single robot to be used flexibly in multiple places of a produc tion seems unfulfilled. If more unskilled workers understood the collaborative r obots and received structured training, they would be capable of programming the robots independently. This could change the current landscape of stationary col laborative robots towards more flexible robot use and thereby increase companies ' internal overall equipment efficiency and competencies. To this end, we identi fy general skills and knowledge for programming a collaborative robot, which hel ps increase the transparency of what novices need to know. We show how such know ledge and skills may be facilitated in a structured training framework, which ef fectively transfers necessary programming knowledge and skills to novices. This framework may be applied to a wider scope of knowledge and skills as the learner progresses. The skills and knowledge that we identify are general across robot platforms, however, collaborative robot interfaces differ. Therefore, a practica l limitation to the approach includes the need for a knowledgeable person on the specific collaborative robot in question in order to create training material i n areas specific to that model. However, with our list of identified skills, it provides an easier starting point."
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