汪潼, 朱世强, 宋伟, 李存军, 施浩磊. 立式罐容量计量中爬壁机器人的路径规划[J]. 机器人, 2024, 46(1): 36-44. DOI: 10.13973/j.cnki.robot.230036
引用本文: 汪潼, 朱世强, 宋伟, 李存军, 施浩磊. 立式罐容量计量中爬壁机器人的路径规划[J]. 机器人, 2024, 46(1): 36-44. DOI: 10.13973/j.cnki.robot.230036
WANG Tong, ZHU Shiqiang, SONG Wei, LI Cunjun, SHI Haolei. Path Planning for Wall-climbing Robot in Volume Measurement of Vertical Tank[J]. ROBOT, 2024, 46(1): 36-44. DOI: 10.13973/j.cnki.robot.230036
Citation: WANG Tong, ZHU Shiqiang, SONG Wei, LI Cunjun, SHI Haolei. Path Planning for Wall-climbing Robot in Volume Measurement of Vertical Tank[J]. ROBOT, 2024, 46(1): 36-44. DOI: 10.13973/j.cnki.robot.230036

立式罐容量计量中爬壁机器人的路径规划

Path Planning for Wall-climbing Robot in Volume Measurement of Vertical Tank

  • 摘要: 针对立式罐容量计量中的需求,设计了一种激光跟踪仪与爬壁机器人相结合的计量方法。为实现高效、高精度的容量计量,基于测点分布规划了一种机器人测量路径。首先,采用2种计算方法分别适应周向、垂向稀疏的测点分布。由于测量路径与计量精度的关系尚不明确,因此创建了罐体模型以分析测点分布对用时、精度的影响,进而确定路径样式及参数。最后,在罐壁点云和某储罐上分别进行仿真和实物实验,提出一个损失函数以评价该路径,并将现场测量结果与全站仪法的结果进行比对。结果表明,使用该路径开展测量的用时短,仿真与实物实验的计量误差均小于0.04%,总体损失小于其他现有计量方法。

     

    Abstract: To meet the requirements of measuring the vertical tank volume, a measurement method combining a laser tracker and a wall-climbing robot is designed. In order to realize efficient and accurate measurement, a measuring path of the robot is planned based on MPD (measuring points distribution). Firstly, two measurement methods are adopted to adapt to the circumferentially and vertically sparse MPD respectively. Since the relationship between the measuring path and accuracy is not clear, a tank model is created to analyze the influence of MPD on the time and accuracy, and then the path pattern and its parameters are determined. Finally, simulation and physical experiments are carried out on the point cloud of a tank wall and a real tank respectively. A loss function is proposed to evaluate the path, and the field measurement results are compared with those of the total station method. The results show that the measurement based on the planned path can be completed quickly, and the measurement errors in both simulation and experiments are less than 0.04%, bringing an overall loss smaller than that of currently used measurement methods.

     

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