基于光学跟踪系统的扩展卡尔曼滤波器提高机器人目标点跟踪的定位精度

IF 4.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
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引用次数: 0

摘要

尽管工业机器人已成功应用于广泛的生产自动化领域,但由于其绝对定位精度较低,在许多高精度任务中仍面临挑战,尤其是在小批量、多品种生产中。为了应对这种快速变化的生产任务,需要一种有效的方法来确定机器人与工件之间的姿态关系,而无需对机器人进行示教等人工干预。为此,本文提出使用扩展卡尔曼滤波器(EKF)和光学跟踪系统来提高机器人的定位精度,并特别关注手臂末端工具的目标点跟踪,这是许多机器人任务的重要组成部分。为此,首先为末端工具推导出一个全面的运动学误差模型,该模型考虑了 Denavit-Hartenberg (D-H) 参数误差、机器人底座定位误差和末端工具安装误差。然后,通过使用光学跟踪系统,可以有效地确定臂端工具相对于工件的姿态。基于 EKF 算法,可以在线估计系统的运动参数误差,以补偿机器人运动过程中目标点的定位误差。仿真和实验测试证明了所提方法的有效性。所提方法利用给定轨迹设计补偿方案,在运动过程中估算机器人的运动参数误差,然后在目标点补偿臂端工具的定位误差。因此,这种方法可以在没有持续反馈的情况下提高机器人的目标点精度,从而实时减少沿轨迹的跟踪误差。这种方法易于实施,适用于小批量、多品种的情况,无需人工干预即可确定机器人与工件之间的姿势关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Positioning accuracy improvement for target point tracking of robots based on Extended Kalman Filter with an optical tracking system

Although industrial robots have been successfully used in a wide spectrum of applications for production automation, they still face challenges for many high precision tasks especially in low-volume high-mix production due to their low absolute positioning accuracy. To respond to such rapidly changing production tasks, an efficient means is required to determine the pose relationship between the robot and the workpiece without human intervention such as teaching the robot. For this purpose, the paper proposes the use of the Extended Kalman Filter (EKF) with an optical tracking system to improve the robot positioning accuracy with a particular focus on the target point tracking of the end-of-arm tool, which is an essential part for many robotic tasks. To this end, a comprehensive kinematic error model is first derived for the end-of-arm tool that accounts for the errors in the Denavit-Hartenberg (D-H) parameters, the positioning errors of the robot base and the end-of-arm tool installation. Then, by using the optical tracking system, the pose of the end-of-arm tool relative to the workpiece can be determined in an efficient way. Based on the EKF algorithm, the kinematic parameter errors of the system can be estimated online to compensate the positioning error of the target point during the robot movement. Simulation and experimental tests have been performed to demonstrate the effectiveness of the proposed method. The proposed approach utilizes the given trajectory to design a compensation scheme where the kinematic parameter errors of the robot are estimated during the motion and then the positioning error of the end-of-arm tool is compensated at the target point. As a result, this approach can improve the target point accuracy of the robot without continuous feedback to reduce the tracking error along the trajectory in real time. It is easy to implement and suitable for low-volume, high-mix scenarios to determine the pose relationship between the robot and the workpiece without human intervention.

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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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