摘要
巡线机器人沿相线行走时必须探测识别各种障碍,并根据障碍类型规划越障行为.针对220 kV架空输电线路的结构特点,利用视觉传感器,设计了基于结构约束的障碍识别算法.算法利用图像的边缘信息,采用改进的基于存在概率图的圆/椭圆检测方法和分层决策机制,以减少自然环境中光线变化和机器人运动对识别质量的影响,满足了巡线机器人的实时越障要求.实验室模拟线路和实际线路实验结果表明,算法能可靠地识别出复杂背景中的防震锤、悬垂线夹和耐张线夹等障碍物.
Power transmission line inspection robot must plan its behaviors to negotiate obstacles according to their types when it is crawling along the power transmission line. For this purpose, based on the structure of a 220 kV transmission line, a structure-constrained obstacle recognition algorithm is designed with machine vision sensors. The algorithm uses an improved existence-probability-map-based circle/ellipse detection method and a hierarchical decision mechanism to reduce the effects of illumination variation and robot motion on obstacle recognition quality, which satisfies the needs of real-time obstacle negotiation of inspection robot. The results of experiments with simulation and real transmission lines show that the algorithm can reliably recognize obstacles such as counterweight, strain clamp, and suspension clamp from cluttered background.
出处
《机器人》
EI
CSCD
北大核心
2007年第1期1-6,共6页
Robot
基金
国家863计划资助项目(2005AA420060)
现场总线北京市重点实验室开放资金资助项目
关键词
障碍识别
圆检测
巡线机器人
霍夫变换
输电线路
obstacle recognition
circle detection
inspection robot
Hough transform
power transmission line
