[1]胡斐,李维嘉,汪潇.基于视觉引导的Delta型并联机器人运动优化[J].机械与电子,2018,(06):71-75.
　HU Fei,LI Weijia,WANG Xiao.Motion Optimization of Delta Parallel Robot Based on Visual Guidance[J].Machinery & Electronics,2018,(06):71-75.
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基于视觉引导的Delta型并联机器人运动优化()
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机械与电子[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2018年06期
页码:
71-75
栏目:
智能工程
出版日期:
2018-06-24

文章信息/Info

Title:
Motion Optimization of Delta Parallel Robot Based on Visual Guidance
文章编号:
1001-2257(2018)06-0071-05
作者:
胡斐1; 李维嘉1; 汪潇1
(1. 华中科技大学船舶与海洋工程学院,湖北 武汉 430074)
Author(s):
HU Fei;  LI Weijia;  WANG Xiao
(School of Naval Architecture & Ocean Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)
关键词:
Delta机器人; 粒子群算法; 运动优化
Keywords:
Delta robot;  particle swarm optimization;  motion optimization
分类号:
TP242.2
文献标志码:
A
摘要:
针对Delta型并联机器人抓取过程中的快速性和稳定性问题，提出一种基于视觉引导的轨迹优化算法。通过获取视觉相机识别出的随机放置于传送带上的工件实时位置，以抓取路径最短和机构平稳性最优为综合优化目标，采用粒子群优化算法对抓取轨迹进行优化。选取工件以正态分布和平均分布2种方式随机分布在传送带上。仿真结果表明，优化后的抓取轨迹在提高抓取效率的同时有效降低了抓取运动对机构末端冲击。最后，通过实验验证了该算法的有效性。
Abstract:
This paper proposes a visual-guided trajectory optimization algorithm to improve the rapidity and stability during the gripping process of Delta parallel robot.?Firstly, the real-time position of the workpiece randomly distributed on the conveyor belt was captured by CCD camera.?Then, the picking and placing trajectory was optimized by using the particle swarm optimization algorithm to determine the shortest path and most stable mechanism.?Finally, the selected workpieces were randomly distributed on the conveyor belt in two ways, namely, the normal distribution and the even distribution. The simulation results show that the optimized trajectory not only improves the efficiency but also effectively reduces the impact on the end of the mechanism.

参考文献/References:

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备注/Memo

备注/Memo:

收稿日期：2018-03-15
作者简介:胡斐(1992-)，男，湖北随州人，硕士研究生，研究方向为计算机控制与仿真研究;李维嘉(1964-)，男，河南郑州人，教授，博士研究生导师，研究方向为液压控制工程、工业机器人等，通信作者;汪潇（1984-），女，湖北汉川人，硕士研究生，研究方向为计算机控制与仿真研究。

更新日期/Last Update: 2019-10-30