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Online Generation of Reachable Grasps for Dexterous Manipulation Using a Representation of the Reachable Workspace

机译:使用可达工作空间的表示,在线生成可达可达掌握的可达操纵

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In service robotic tasks, the ability to grasp and handle objects is mandatory. Short response times with respect to execution of commanded tasks are necessary. Planning in general and grasp planning in particular should happen online. We extend the online grasp planner by Borst et al. [1] to generate reachable grasps while preserving the integrity and modularity of the grasp planner. To achieve this a representation of the reachable space of a robot arm is used to determine a grasp's reachability. Furthermore we show the influence of obstacles on the reachability throughout the workspace. A method to include obstacles into the representation of reachability is sketched. The resulting representation is used by the grasp planner. The performance of the algorithms is evaluated by measuring their computation times. Even in the worst case our grasp planner outperforms comparable state of the art approaches.
机译:在服务机器人任务中,掌握和处理对象的能力是强制性的。需要对命令任务执行的短响应时间是必要的。规划一般并掌握规划,特别是在线发生。我们通过Borst等人扩展了在线掌握策划人。 [1]在保留掌握规划器的完整性和模块的同时产生可达可达的掌握。为了实现这一点,可以使用机器人臂的可达空间的表示来确定掌握的可达性。此外,我们展示了障碍对整个工作空间可达性的影响。速写了将障碍物纳入可达性表示的方法。掌握规划师使用得到的表示。通过测量其计算时间来评估算法的性能。即使在最坏的情况下,我们的掌握规划师也优于艺术方法的可比性。

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