The application of robotic solutions to small-batch production is challenging: economical constraints tend to dramatically limit the time for setting up new batches. Organizing robot tasks into modular software components, called skills, and allowing the assignment of multiple concurrent tasks to a single robot is potentially game-changing. However, due to cycle time constraints, it may be necessary for a skill to take over without waiting on another to terminate, and the available literature lacks a systematic approach in this case. In the present article, we fill the gap by (a) establishing the specifications of skills that can be sequenced with partial executions, (b) proposing an implementation based on the combination of finite-state machines and behavior trees, and (c) demonstrating the benefits of such skills through extensive trials in the environment of ARIAC (Agile Robotics for Industrial Automation Competition).
翻译:将机器人解决方案应用于小批量生产具有挑战性:经济限制往往会极大地限制建立新的批次的时间。将机器人任务组织成模块化软件组件,称为技能,允许将多重并行任务分配给一个机器人,这有可能改变游戏模式。然而,由于周期性时间限制,可能需要一种技能在不等待另一个机器人终止的情况下接管,而现有文献在这方面缺乏系统的方法。在目前这篇文章中,我们通过(a) 确定部分处决可以排序的技能规格,(b) 提出基于有限状态机器与行为树相结合的实施,以及(c) 通过在ARIAC环境中的广泛试验(工业自动化竞赛的大型机器人)展示这种技能的好处,填补了这一空白。