Despite cobots have high potential in bringing several benefits in the manufacturing and logistic processes, but their rapid (re-)deployment in changing environments is still limited. To enable fast adaptation to new product demands and to boost the fitness of the human workers to the allocated tasks, we propose a novel method that optimizes assembly strategies and distributes the effort among the workers in human-robot cooperative tasks. The cooperation model exploits AND/OR Graphs that we adapted to solve also the role allocation problem. The allocation algorithm considers quantitative measurements that are computed online to describe human operator's ergonomic status and task properties. We conducted preliminary experiments to demonstrate that the proposed approach succeeds in controlling the task allocation process to ensure safe and ergonomic conditions for the human worker.
翻译:尽管科博特人具有在制造和后勤过程中带来若干好处的巨大潜力,但在变化的环境中迅速(重新)部署仍然有限。为了能够迅速适应新的产品需求,提高工人对分配的任务的适应能力,我们提议了一种新颖的方法,优化组装战略,并在从事人-机器人合作任务的工人中分配这种努力。合作模式利用和/或我们为解决角色分配问题而调整的图表。分配算法考虑了在网上计算的数量测量,以描述人类操作者的人类基因学状况和任务特性。我们进行了初步实验,以证明拟议的方法成功地控制了任务分配过程,确保了人类工人的安全和人类基因条件。