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Reactive motion planning using time-layered C-spaces for a collaborative robot PaDY
Advanced Robotics ( IF 1.4 ) Pub Date : 2021-03-10 , DOI: 10.1080/01691864.2021.1896381
Hisaka Wada 1 , Jun Kinugawa 1 , Kazuhiro Kosuge 1
Affiliation  

A reactive motion-planning for collaborative robots using the time-layered C-spaces (TLC-spaces) is proposed in this paper. First, the time-augmented C-space (TAC-space) is introduced. TAC-space is an implementation of the configuration-time space with multiple moving obstacles [Latombe JC. Robot motion planning. Kluwer Academic; 1991. p. 22, 23]. The TAC-space is obtained by stacking the current and predicted future C-spaces along the time axis using predicted motions of the obstacles. Then, TLC-spaces is constructed as the collection of only those C-spaces in the TAC-space that are relevant to the motion planning with moving obstacles. The trajectory that reaches the goal configuration at the specified target time is generated under dynamic constraints including robot velocity and acceleration. We focus on a collaborative robot, PaDY, whose task is to deliver tools and parts to the worker in a factory. Similar to an actual assembly process in an automobile production system, six scenarios are selected for the evaluation of the proposed motion planning method. The simulation results using the real-life motion of workers show that the computation time required for the proposed motion planning using TLC-spaces is shorter than that of our previous method using TAC-space. The experimental results show that the proposed method is applicable to PaDY in human environments.



中文翻译:

使用时间分层C空间进行协作机器人PaDY的反应性运动计划

本文提出了一种基于时空C空间(TLC-spaces)的协作机器人反应运动规划方法。首先,介绍了时间扩展的C空间(TAC-space)。TAC空间是具有多个移动障碍物的配置时空间的一种实现方式[Latombe JC。机器人运动计划。Kluwer学术;1991年。22,23]。通过使用障碍物的预测运动沿时间轴堆叠当前和预测的未来C空间来获得TAC空间。然后,将TLC空​​间构造为TAC空间中仅与那些具有移动障碍物的运动计划相关的C空间的集合。在指定的目标时间达到目​​标配置的轨迹是在包括机器人速度和加速度在内的动态约束下生成的。我们专注于协作机器人PaDY,他们的任务是向工厂的工人交付工具和零件。与汽车生产系统中的实际组装过程相似,选择了六个方案来评估所提出的运动计划方法。使用工人实际运动的仿真结果表明,使用TLC空间进行拟议的运动计划所需的计算时间比使用TAC空间的先前方法所需的计算时间短。实验结果表明,该方法适用于人类环境中的PaDY。使用工人实际运动的仿真结果表明,使用TLC空间进行拟议的运动计划所需的计算时间比使用TAC空间的先前方法所需的计算时间短。实验结果表明,该方法适用于人类环境中的PaDY。使用工人实际运动的仿真结果表明,使用TLC空间进行拟议的运动计划所需的计算时间比使用TAC空间的先前方法所需的计算时间短。实验结果表明,该方法适用于人类环境中的PaDY。

更新日期:2021-04-30
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