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Robot vision to recognize both object and rotation for robot pick-and-place operation

机译:机器人视觉识别物体和旋转,从而实现机器人的拾取和放置操作

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This paper presents a robot vision system to recognize both different target objects and their poses that can be incorporated in robot programming by demonstration (robot PbD). In recent years, robot PbD has become a popular topic in the field of robotics. Programming robots is a time-consuming process and requires technical knowledge. However, robot task programming will be simplified by using a vision system to analyze human demonstration. Usually, design of a user-friendly human-robot interaction interface is crucial to implement the robot PbD process. We take pick-and-place operation as an example of robot PbD. Several objects are placed on a table without overlapping, and people pick one of them to other place, one after another. Before learning from human demonstration, if the robot can obtain initial information, e.g., to recognize the target object and to estimate its pose, it helps robot to refine its following decision, such as selecting the gripper type or the grip angle. Thus the authors develop the robot vision ads the first step to realize such working robot. The developed vision system has advantage of interactive trainability with the help of the proposed graphical user interface (GUI), in which the interpretable features can be easily selected by ordinary users. We also propose a simple scale-invariant pose estimation method. Experimental results support feasibility and effectiveness of the system.
机译:本文提出了一种机器人视觉系统,该系统可以识别不同的目标对象及其姿势,并且可以通过演示将其纳入机器人编程中(机器人PbD)。近年来,机器人PbD已成为机器人技术领域的热门话题。对机器人进行编程是一个耗时的过程,并且需要技术知识。但是,将通过使用视觉系统分析人类演示来简化机器人任务的编程。通常,用户友好的人机交互界面的设计对于实现机器人PbD流程至关重要。我们将取放操作作为机器人PbD的示例。几个物体放在桌子上时没有重叠,人们将其中一个物体一个接一个地移到另一个地方。在从人类演示中学习之前,如果机器人可以获取初始信息(例如,识别目标对象并估计其姿态),则可以帮助机器人完善其后续决策,例如选择抓取器类型或抓取角度。因此,作者开发机器人视觉广告是实现这种工作机器人的第一步。所开发的视觉系统在建议的图形用户界面(GUI)的帮助下具有交互式培训的优势,其中普通用户可以轻松选择可解释的功能。我们还提出了一种简单的尺度不变姿态估计方法。实验结果证明了该系统的可行性和有效性。

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