In pace with the electronic technology development and the production technology improvement, industrial robot Give Scope to the Advantage in social services and industrial production. However, due to long-term mechanical wear and structural deformation, the absolute positioning accuracy is low, which greatly hinders the development of manufacturing industry. Calibrating the kinematic parameters of the robot is an effective way to address it. However, the main measuring equipment such as laser trackers and coordinate measuring machines are expensive and need special personnel to operate. Additionally, in the measurement process, due to the influence of many environmental factors, measurement noises are generated, which will affect the calibration accuracy of the robot. Basing on these, we have done the following work: a) developing a robot calibration method based on plane constraint to simplify measurement steps; b) employing Square-root Culture Kalman Filter (SCKF) algorithm for reducing the influence of measurement noises; c) proposing a novel algorithm for identifying kinematic parameters based on SCKF algorithm and Levenberg Marquardt (LM) algorithm to achieve the high calibration accuracy; d) adopting the dial indicator as the measuring equipment for slashing costs. The enough experiments verify the effectiveness of the proposed calibration algorithm and experimental platform.
翻译:由于长期机械磨损和结构变形,绝对定位精确度较低,这严重阻碍了制造业的发展。校准机器人的动力参数是解决这一问题的有效方法。但是,主要测量设备,如激光追踪器和协调测量机器,费用昂贵,需要特殊人员操作。此外,在测量过程中,由于许多环境因素的影响,产生了测量噪音,这将影响机器人的校准准确性。我们在此基础上做了以下工作:(a) 开发基于飞机限制的机器人校准方法,以简化测量步骤;(b) 采用平方文化卡尔曼过滤法(SCKF)算法,以减少测量噪音的影响;(c) 提出根据SCKF算法和Levenberg Marqurdt(LM)算法确定运动参数的新算法,以达到高校准准确性;d) 采用拨号指标,作为测量实验室成本的校准设备。进行足够的实验,以核实拟议校准。