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A fast, GPU-based geometrical placement planner for unknown sensor-modelled objects and placement areas

机译:一种基于GPU的快速几何布局计划器,用于未知的传感器建模对象和放置区域

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A Personal Robot should be able to handle unknown objects in unknown environments. For a manipulation task the question what to do with an object once it had been grasped is one of the most essential ones beside the grasping task itself. Moreover, the planning time should be at least as fast as the time the robot needs for its motions. We propose a fast placement planner for sensor-modelled objects in complex environments. The planner computes a stable position and orientation for the object in the environment. The algorithm uses only geometric information, most notably no force or torque sensor is required. In particular, we introduce a novel approach regarding the pose computation. By means of experiments with various household objects the robustness and performance are validated. Further on, we compare our approach with a pose computation using a physics simulation framework.
机译:个人机器人应该能够在未知环境中处理未知对象。对于操作任务,一旦抓到对象该如何处理是除了抓取任务本身之外最重要的问题之一。此外,计划时间应至少与机器人运动所需的时间一样快。我们为复杂环境中的传感器建模对象提出了一种快速放置计划器。计划者为环境中的对象计算稳定的位置和方向。该算法仅使用几何信息,最显着的是不需要力或扭矩传感器。特别是,我们介绍了一种有关姿势计算的新颖方法。通过各种家用物品的实验,验证了其坚固性和性能。进一步,我们将使用物理模拟框架的姿势计算与我们的方法进行了比较。

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