Abstract: 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.