Automatic Obstacle-Crossing Planning for a Transmission Line Inspection Robot Based on Multisensor Fusion

Abstract

Accurate obstacle detection and proper behavior planning are key factors in the success of transmission line inspection robots. To achieve the autonomous location and identification of line obstacles in the operation of transmission line inspection robots, we propose a method in which information from various sensors is used to control a robot such that it can reliably and stably approach, locate, and identify obstacles. The accuracy and real-time requirements of obstacle information in the autonomous operation of the inspection robot are analyzed, a multi-sensor integrated structure for line obstacle location and identification is proposed, and an obstacle location and identification algorithm is designed for each stage. The principle of monocular vision ranging is used to control the robot such that it approaches obstacles and enters the short-range location stage, where the reliable location of obstacles is achieved via collision-encoder-current sensor data fusion. Obstacles are identified and the identification results are combined with those of the approaching rolling phase. The robot state vector is constructed according to the obstacle detection information and information measured by the robot sensors. Based on the current state vector, combined with the robot obstacle surmounting process, an obstacle surmounting behavior planning method based on multi-sensor fusion is implemented. Experiments were conducted using laboratory-simulated lines to verify the effectiveness of the proposed method for obstacle detection and behavior planning during transmission line inspection.