Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (17): 260-268.DOI: 10.3778/j.issn.1002-8331.2007-0449

Previous Articles     Next Articles

Optimization of Robot Delay Using Events and Deadline Control

XU Yangyang,LI Wei,WANG Jie   

  1. 1.School of Mechanical and Electrical Engineering, Zhengzhou University of Industrial Technology, Zhengzhou 451100, China
    2.School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China
  • Online:2021-09-01 Published:2021-08-30

利用事件和期限驱动对机器人延时的优化

许洋洋,李伟,王杰   

  1. 1.郑州工业应用技术学院 机电工程学院,郑州 451100
    2.郑州大学 电气工程学院,郑州 450001

Abstract:

With the advancement of science and technology, the field of robotics has developed rapidly. In order to better adapt robots to complex working environments, it is necessary to further improve the perception performance of robots. Most robots use vision as a means of perception. However, because the image contains a large amount of data and it takes a lot of time to process the data, the robot has a significant delay, which leads to a decrease in the performance of the robot. Therefore, in order to solve this problem, a deadline-driven and event-driven control method is proposed. The core of the method is to apply the idea of model-based control design method to the robot motion control based on the vision-based self-positioning algorithm. At the same time, the delay of a simple positioning algorithm based on random sample consistency is considered. Experimental results prove that the proposed deadline-driven and event-driven control design is significantly better than the traditional cycle control.

Key words: image processing, deadline-driven control, event-driven control, delay optimization, machine vision

摘要:

随着科技的进步,机器人领域得到了飞速发展,为了更好地让机器人适应复杂工作环境,需要进一步提高机器人的感知性能。大多数机器人采用视觉作为感知手段。但由于图像中包含大量数据以及处理这些数据需要花费大量时间,导致了机器人有显著的延时,从而导致机器人性能的下降。因此,为了解决这一问题,提出了一种基于期限驱动和事件驱动控制方法,该方法的核心是把基于模型的控制设计方法的思想应用到基于视觉的自定位算法的机器人运动控制中。同时考虑了一种简单的基于随机样本一致性的定位算法的延时情况。实验结果证明,提出的期限驱动和事件驱动控制设计明显优于传统的周期控制。

关键词: 图像处理, 期限驱动控制, 事件驱动控制, 延时优化, 机器视觉