We develop two cooperative robots for power transmission lines (PTLs) inspection - a light climbing robot (CBR) which can stably move on the overhead ground wire (OGW) for sensor data collection and an unmanned aerial vehicle (UAV) with a grabbing mechanism, which can automatically put the CBR on the OGW and take it off. In order to guarantee the safety, the mechanical structures of the connectors are designed in the shape of a trumpet. Further, a self-locked structure of the CBR is developed to automatically seize and release the OGW. For autonomous navigation, the UAV is equipped with a movable sliding rail and a 2D Laser Range Finder (LRF). The LRF can not only detect the position and orientation of the OGW but also detect the top beam of the CBR and the grabbing position in it. Furthermore, the action of the grabbing mechanism is automatically triggered by a microswitch. Finally, by the developed UAV and CBR platforms, we test the whole loading and unloading strategy in an artificially constructed PTLs environment outdoors and achieve an encouraging result1. Combining the flexible motion of the UAV and the high inspection accuracy of the CBR, the CBR can negotiate any obstacle by flying and abandon the traditional heavy obstacle crossing mechanism to effectively realize close-proximity inspection. Due to the light weight and low power consumption, the CBRs can be deployed once in many power corridors to conduct a long-term inspection.

This paper proposes a unique and robust UAV autonomous navigation approach along one side of overhead transmission lines for inspection. To this end, we establish a perspective model and develop a novel Pan/Tilt monocular-based navigation scheme. Simultaneously, the following three key issues are addressed. First, to locate the effective landmark - transmission tower timely and reliably, we customize a neural network for tower detection and combine it with a fast and smooth tracking. Second, to provide UAV with a robust and precise heading, we detect the transmission lines and compute and optimize their vanishing point. Third, to keep a safe distance from transmission lines, we optimize a homography matrix to restore the parallel nature of transmission lines and perceive the distance variation by a point set registration model. Finally, by the designed UAV platform, we test the whole system in a real-world transmission-line inspection scenario under different weather condition and achieve an encouraging result. Our approach provides great flexibility for refined inspection and effectively improves inspection safety.