考虑关节柔性误差的机器人参数辨识方法研究
发布时间：2019-06-21 15:54
【摘要】：考虑到工业机器人绝对定位精度较低,无法满足高精度加工的需要,故提出了一种综合型误差补偿方法。以改进的D-H模型为基础,建立机器人末端工具中心点的距离误差模型,同时对主要受力关节2和3由于自重或者外加负载产生的柔性变形误差进行了研究,建立了柔性误差模型,最后以激光跟踪仪作为测量设备,利用最小二乘法对模型进行求解,通过修正控制器参数补偿误差提高机器人定位精度。经过补偿,自主研发的机器人定位精度有明显的提高,从之前的3.548 mm降至0.939 mm。
[Abstract]:In view of the fact that the absolute positioning accuracy of the industrial robot is low and the need for high-precision machining cannot be met, a comprehensive error compensation method is proposed. based on the improved D-H model, the distance error model of the center point of the end tool of the robot is established, and the flexible deformation error generated by the self-weight or the applied load of the main bearing joints 2 and 3 is researched, a flexible error model is established, Finally, using the laser tracker as the measuring equipment, the model is solved by the least square method, and the positioning accuracy of the robot is improved by correcting the controller parameter compensation error. After compensation, the positioning accuracy of the self-developed robot is obviously improved, and it is reduced to 0.939 mm from the previous 3.548 mm.
【作者单位】： 江南大学机械工程学院;
【基金】：国家自然科学基金项目(61305016) 江苏省科技重点支撑计划项目(BE2013003-3) 江苏省高校研究生科研创新项目(KYLX-1116)资助
【分类号】：TP242
[Abstract]:In view of the fact that the absolute positioning accuracy of the industrial robot is low and the need for high-precision machining cannot be met, a comprehensive error compensation method is proposed. based on the improved D-H model, the distance error model of the center point of the end tool of the robot is established, and the flexible deformation error generated by the self-weight or the applied load of the main bearing joints 2 and 3 is researched, a flexible error model is established, Finally, using the laser tracker as the measuring equipment, the model is solved by the least square method, and the positioning accuracy of the robot is improved by correcting the controller parameter compensation error. After compensation, the positioning accuracy of the self-developed robot is obviously improved, and it is reduced to 0.939 mm from the previous 3.548 mm.
【作者单位】： 江南大学机械工程学院;
【基金】：国家自然科学基金项目(61305016) 江苏省科技重点支撑计划项目(BE2013003-3) 江苏省高校研究生科研创新项目(KYLX-1116)资助
【分类号】：TP242
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