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A robotic grasping approach with elliptical cone-based potential fields under disturbed scenes
International Journal of Advanced Robotic Systems ( IF 2.3 ) Pub Date : 2021-02-16 , DOI: 10.1177/1729881420985739
Wenjie Geng 1 , Zhiqiang Cao 1 , Zhonghui Li 2 , Yingying Yu 1 , Fengshui Jing 1 , Junzhi Yu 3
Affiliation  

Vision-based grasping plays an important role in the robot providing better services. It is still challenging under disturbed scenes, where the target object cannot be directly grasped constrained by the interferences from other objects. In this article, a robotic grasping approach with firstly moving the interference objects is proposed based on elliptical cone-based potential fields. Single-shot multibox detector (SSD) is adopted to detect objects, and considering the scene complexity, Euclidean cluster is also employed to obtain the objects without being trained by SSD. And then, we acquire the vertical projection of the point cloud for each object. Considering that different objects have different shapes with respective orientation, the vertical projection is executed along its major axis acquired by the principal component analysis. On this basis, the minimum projected envelope rectangle of each object is obtained. To construct continuous potential field functions, an elliptical-based functional representation is introduced due to the better matching degree of the ellipse with the envelope rectangle among continuous closed convex curves. Guided by the design principles, including continuity, same-eccentricity equivalence, and monotonicity, the potential fields based on elliptical cone are designed. The current interference object to be grasped generates an attractive field, whereas other objects correspond to repulsive ones, and their resultant field is used to solve the best placement of the current interference object. The effectiveness of the proposed approach is verified by experiments.



中文翻译:

扰动场景下基于椭圆锥势场的机器人抓取方法

基于视觉的抓握在提供更好服务的机器人中起着重要作用。在受干扰的场景下仍然具有挑战性,因为受其他对象的干扰无法直接抓住目标对象。在本文中,提出了一种基于椭圆圆锥形势场的,首先移动干涉对象的机器人抓取方法。采用单发多盒检测器(SSD)检测物体,考虑到场景的复杂性,还采用欧几里得聚类获取物体,而无需经过SSD训练。然后,我们获取每个对象的点云的垂直投影。考虑到不同的物体在各自的方向上具有不同的形状,垂直投影沿着通过主成分分析获得的主轴进行。在此基础上,获得每个对象的最小投影信封矩形。为了构造连续势场函数,由于椭圆与连续闭合凸曲线之间的包络矩形的匹配程度更好,因此引入了基于椭圆的函数表示。遵循连续性,同心性等价性和单调性等设计原则,设计了基于椭圆锥的势场。要抓取的当前干扰对象会产生一个吸引场,而其他对象对应于排斥对象,它们的合成场将用于解决当前干扰对象的最佳位置。实验证明了该方法的有效性。为了构造连续势场函数,由于椭圆与连续闭合凸曲线之间的包络矩形的匹配程度更好,因此引入了基于椭圆的函数表示。遵循连续性,同心性等价性和单调性等设计原则,设计了基于椭圆锥的势场。要抓取的当前干扰对象会产生一个吸引场,而其他对象对应于排斥对象,它们的合成场将用于解决当前干扰对象的最佳位置。实验证明了该方法的有效性。为了构造连续势场函数,由于椭圆与连续闭合凸曲线之间的包络矩形的匹配程度更好,因此引入了基于椭圆的函数表示。遵循连续性,同心性等价性和单调性等设计原则,设计了基于椭圆锥的势场。要抓取的当前干扰对象会产生一个吸引场,而其他对象对应于排斥对象,它们的合成场将用于解决当前干扰对象的最佳位置。实验证明了该方法的有效性。由于椭圆与连续闭合凸曲线之间的包络矩形具有更好的匹配度,因此引入了基于椭圆的功能表示。遵循连续性,同心性等价性和单调性等设计原则,设计了基于椭圆锥的势场。要抓取的当前干扰对象会产生一个吸引场,而其他对象对应于排斥对象,它们的合成场将用于解决当前干扰对象的最佳位置。实验证明了该方法的有效性。由于椭圆与连续闭合凸曲线之间的包络矩形具有更好的匹配度,因此引入了基于椭圆的功能表示。遵循连续性,同心性等价性和单调性等设计原则,设计了基于椭圆锥的势场。要抓取的当前干扰对象会产生一个吸引场,而其他对象对应于排斥对象,它们的合成场将用于解决当前干扰对象的最佳位置。实验证明了该方法的有效性。要抓取的当前干扰对象会产生一个吸引场,而其他对象对应于排斥对象,它们的合成场将用于解决当前干扰对象的最佳位置。实验证明了该方法的有效性。要抓取的当前干扰对象会产生一个吸引场,而其他对象对应于排斥对象,它们的合成场将用于解决当前干扰对象的最佳位置。实验证明了该方法的有效性。

更新日期:2021-02-16
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