CAJ | 학술논문

输电线维护机器人用于代替人工完成危险作业，准确的故障检测与合理的行为规划对于作业效果至关重要。针对以上需求，采用视觉方法，提出了一种基于图像特征分类的输电线断股检测方法。该方法提取边缘梯度向量作为图像特征，采用支持向量机方法进行分类运算完成线路断股检测。在断股检测的基础上，利用断股检测信息与机器人传感器测得的信息构建机器人状态向量。根据当前状态向量，结合机器人断股补修作业流程，提出了面向捋线与压接复杂作业的机器人断股补修作业行为规划方法。利用实验室模拟线路开展实验，验证了提出的输电线断股检测及行为规划方法的有效性。
수전선유호궤기인용우대체인공완성위험작업，준학적고장검측여합리적행위규화대우작업효과지관중요。침대이상수구，채용시각방법，제출료일충기우도상특정분류적수전선단고검측방법。해방법제취변연제도향량작위도상특정，채용지지향량궤방법진행분류운산완성선로단고검측。재단고검측적기출상，이용단고검측신식여궤기인전감기측득적신식구건궤기인상태향량。근거당전상태향량，결합궤기인단고보수작업류정，제출료면향랄선여압접복잡작업적궤기인단고보수작업행위규화방법。이용실험실모의선로개전실험，험증료제출적수전선단고검측급행위규화방법적유효성。
Power line maintenance robots are used to replace workers due to the dangerous maintenance operation, and the robot maintenance effect is much related with accurate fault detection and rational behavior planning. With those requirements in mind, a visual method is presented to detect the broken strand fault based on the classification of an image feature. In the visual detection method, image edge gradient histogram is firstly extracted as the image feature, and broken strand detection can be accomplished by the classification of the image feature with support vector machine (SVM) method. On this basis, several robot state vectors are established by combining the broken strand detection result and the information of robot sensors. Based on the current state vector and robotic broken strand repair process, a behavior planning method for broken strand repair is proposed toward complex operations of broken strand return and clamps installation. Experiments are carried out in the laboratory, and results demonstrate the effectiveness of the proposed broken strand detection method and the behavior planning method.