基于相机的工业机器人小批量高变型制造路径规划

Peter Weßeler, Benjamin Kaiser, Jürgen te Vrugt, A. Lechler, A. Verl
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引用次数: 3

摘要

在过去的几年里,工业机器人的购置成本一直在稳步下降。然而,在准备复杂机器人任务所需的努力方面,它们仍然面临着显著的缺点,这导致这些系统迄今为止很少出现在主要关注小批量、高变型制造的中小型企业(SME)中。在本文中,我们提出了一个基于相机的路径规划框架,该框架允许在动态环境中快速准备和执行机器人任务,从而减少规划开销,快速生成程序并降低成本,从而克服了在中小企业中使用工业机器人进行自动化的主要障碍,重点是小批量和高变型制造。该框架分不同的步骤解决存在的问题。工件的精确位置和方向由光学传感器扫描的三维环境模型确定。将检索到的信息用于规划满足特定机器人任务边界条件的无碰撞路径。通过一个案例分析,实验证明了该框架的潜力和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Camera based path planning for low quantity - high variant manufacturing with industrial robots
The acquisition costs for industrial robots have been steadily decreasing in past years. Nevertheless, they still face significant drawbacks in the required effort for the preparation of complex robot tasks which causes these systems to be rarely present so far in small and medium-sized enterprises (SME) that focus mainly on small volume, high variant manufacturing. In this paper, we propose a camera-based path planning framework that allows the fast preparation and execution of robot tasks in dynamic environments which leads to less planning overhead, fast program generation and reduced cost and hence overcomes the major impediments for the usage of industrial robots for automation in SMEs with focus on low volume and high variant manufacturing. The framework resolves existing problems in different steps. The exact position and orientation of the workpiece are determined from a 3D environment model scanned by an optical sensor. The so retrieved information is used to plan a collision-free path that meets the boundary conditions of the specific robot task. Experiments show the potential and effectiveness of the the framework presented here by evaluating a case study.
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