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Control of a soft-bodied XY peristaltic table for delicate sorting

机译:控制XY蠕动床身以进行精细分类

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A demand for a soft body robotic h a s become widely apparent especially in industrial sectors to accomplish the rotation of a variety of organic matter. The inaccuracy of the classical robots in the handling of many organic objects such as fruits or eggs in production lines has triggered the necessity for soft body robotics. In this paper, we introduce a hybrid robotic prototype (X-Y soft-bodied peristaltic table) combining soft and hard robotics techniques with cutting-edge design in its physical stature, so as to control its 25 motors and to be autonomous. These 25 motors are capable of generating peristaltic motion in the soft layers of the table surface, thus providing a physical force that transports delicate objects. Two control systems have been developed to validate the industrial potential of a peristaltic XY table. The first system is a dynamic real-time path planning program that has been written to determine the shortest path from an object on the table's surface to a target position selected by the user; the second system is an artificial neural network (ANN) that has been developed to estimate the relationship between the table's actuation pattern and the corresponding surface deformation.
机译:对软体机器人的需求已变得十分明显,特别是在工业领域中,以完成各种有机物的旋转。传统机器人在生产线中处理许多有机物体(例如水果或鸡蛋)时的不精确性触发了软体机器人的必要性。在本文中,我们介绍了一种混合机器人原型(X-Y软体蠕动工作台),该原型将软,硬机器人技术与尖端设计相结合,使其物理身材得以控制,从而能够控制25个电机并实现自主控制。这25个电机能够在工作台表面的软层中产生蠕动,从而提供了一种物理力来运输精致的物体。已经开发出两个控制系统来验证蠕动XY工作台的工业潜力。第一个系统是动态实时路径规划程序,已编写该程序以确定从桌子表面上的物体到用户选择的目标位置的最短路径;第二个系统是一个人工神经网络(ANN),用于估计工作台的驱动模式与相应的表面变形之间的关系。

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