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Multi-goal path planning for industrial robots

机译：工业机器人的多目标路径规划

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A new problem for the automated off-line programming of industrial robot application is investigated. The Multi-Goal Path Planning is to find the collision-free path connecting a set of goal poses and minimzing e.g. the total path length. Our solution is based on an earlier reported path planner for industrial robot arms with 6 degrees-of-freedom in an on-line given 3D environment. To control the path planner, four different goal selection methods are introduced and compared. While the Random and the Nearest Pair Selection methods can be used with any path planner, the Nearest Goal and the Adaptive Pair Selection method are favorable for our planner. With the latter two goal selection methods, the Multi-Goal Path Planning task can be significantly accelerated, because they are able to automatically solve the simplest path planning problems first. Summarizing, compared to Random or Nearest Pair Selection, this new Multi-Goal Path Planning approach results in a further cost reduction of the programming phase.
机译：研究了工业机器人应用的自动化离线编程的新问题。多目标路径规划旨在找到连接一组目标姿势并最小化目标位置的无碰撞路径。总路径长度。我们的解决方案基于先前报道的针对在线给定3D环境中具有6自由度的工业机器人手臂的路径规划器。为了控制路径规划器，引入并比较了四种不同的目标选择方法。虽然随机和最接近对选择方法可以与任何路径规划器一起使用，但是最接近目标和自适应对选择方法对我们的规划者而言是有利的。使用后两种目标选择方法，可以大大加速“多目标路径规划”任务，因为它们能够首先自动解决最简单的路径规划问题。总而言之，与随机或最近配对选择相比，这种新的多目标路径规划方法可进一步降低编程阶段的成本。

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