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基于双目视觉与ROS的机器人去板坯毛刺方法

Method of Robot Removal Slab Burrs Based on Binocular Vision and ROS

  • 摘要: 针对传统钢铁行业板坯去毛刺方法无法满足自动化生产的需求,提出基于双目视觉定位的机器人去板坯毛刺方法。在机器人操作系统(ROS)框架下配置所需工作站的仿真模型;通过加速分割检测特征角点检测算法对尺度不变特征变换算法进行改进,采用最近邻、次近邻比值法得到匹配可靠性最高的角点,利用以角点为中心的圆形区域筛选轨迹规划所需的有效角点;根据双目视觉获取的有效角点三维信息对机器人切割作业进行轨迹规划。结果表明,该方法便捷有效,角点定位准确,测量误差保持在合理范围内。通过完整地模拟双目视觉机器人切割板坯毛刺的历程,验证了双目视觉用于引导机器人去除板坯毛刺的可行性。

     

    Abstract: Aiming to the removal slab burr methods in traditional steel industry cannot meet the needs of automatic production, the method of robot removal slab burr based on binocular vision positioning was proposed. The simulation model of the required workstation was configured under the framework of the robot operating system (ROS). The scale-invariant feature transform algorithm was improved through the features from accelerated segment test corner detection algorithm. The nearest neighbor and next nearest neighbor ratio method was used to obtain the corners which had the highest matching reliability, and then the circular region centered on the corners was used to screen the effective corners required for trajectory planning. According to the effective corner 3D information obtained by binocular vision, the trajectory planning of robot cutting operation was carried out. The results show that the method is convenient and effective, corner locating is accurate, and the measurement error is within a reasonable range. The possibility for guidance of robot removal slab burrs is verified by simulating the process of robot cutting slab burr integrated with binocular vision.

     

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