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

Ryman Hashem, B. Smith, David Browne, Weiliang Xu, M. Stommel
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引用次数: 5

Abstract

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.
控制一个柔软的XY蠕动工作台,用于精细的分类
特别是在工业领域,对软体机器人的需求越来越明显,以完成各种有机物质的旋转。传统机器人在生产线上处理水果、鸡蛋等许多有机物体时的不准确性引发了软体机器人技术的必要性。本文介绍了一种结合软硬机器人技术,在外形上采用尖端设计的混合机器人样机(X-Y软体蠕动工作台),实现了对25个电机的控制和自主。这25个马达能够在桌子表面的柔软层中产生蠕动运动,从而提供物理力量来运输精致的物体。已经开发了两个控制系统来验证蠕动XY表的工业潜力。第一个系统是动态实时路径规划程序,用于确定从工作台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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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