论文标题
机器人质量检查的覆盖路径计划，并控制了测量不确定性
Coverage Path Planning for Robotic Quality Inspection with Control on Measurement Uncertainty
论文作者
论文摘要
安装在机器人上的光学扫描仪通常用于质量检查中，例如验证板结构的尺寸规范。覆盖路径计划（CPP）显着影响机器人质量检查的准确性和效率。传统的CPP策略着重于最大程度地减少在全面覆盖范围检查的条件下，机器人的观点数量或旅行距离。在自由形式的表面检查中，在收集扫描数据时的测量不确定性较少。为了解决这个问题，提出了一种具有最佳观点抽样策略的新型CPP方法，以将关键测量点（MP）的测量不确定性（MPS）纳入自由形式的表面检查中。首先，根据MP的公差规格计算了可行的测量不确定性范围。考虑到MPS的测量不确定性和可见性，生成了最初的可行视点集。然后，构建了检查成本函数，以评估所选观点的数量以及所有选定观点的视图（FOV）中的平均测量不确定性。之后，提出了一种增强的快速探索随机树（RRT*）算法，用于使用检查成本函数和CPP优化的观点采样。已经进行了案例研究，包括模拟测试和检查实验，以评估所提出方法的有效性。结果表明，与基准方法相比，关键MP的扫描精度得到显着提高。
The optical scanning gauges mounted on the robots are commonly used in quality inspection, such as verifying the dimensional specification of sheet structures. Coverage path planning (CPP) significantly influences the accuracy and efficiency of robotic quality inspection. Traditional CPP strategies focus on minimizing the number of viewpoints or traveling distance of robots under the condition of full coverage inspection. The measurement uncertainty when collecting the scanning data is less considered in the free-form surface inspection. To address this problem, a novel CPP method with the optimal viewpoint sampling strategy is proposed to incorporate the measurement uncertainty of key measurement points (MPs) into free-form surface inspection. At first, the feasible ranges of measurement uncertainty are calculated based on the tolerance specifications of the MPs. The initial feasible viewpoint set is generated considering the measurement uncertainty and the visibility of MPs. Then, the inspection cost function is built to evaluate the number of selected viewpoints and the average measurement uncertainty in the field of views (FOVs) of all the selected viewpoints. Afterward, an enhanced rapidly-exploring random tree (RRT*) algorithm is proposed for viewpoint sampling using the inspection cost function and CPP optimization. Case studies, including simulation tests and inspection experiments, have been conducted to evaluate the effectiveness of the proposed method. Results show that the scanning precision of key MPs is significantly improved compared with the benchmark method.
