| Domestic power lines are located in complex terrain with harsh natural environment.Regular inspection of power grid equipment is needed to eliminate potential hazards in time.The traditional manual inspection line has disadvantages with high labor intensity,low efficiency of the line inspection and low inspection data accuracy.The development of UAV technology provides a new method for the inspection of high altitude lines,and using quadcopter to patrol the lines has the characteristics of small casualty risk,low cost and good motor performance,etc.The automatic obstacle avoidance system provides the safety guarantee for the quadcopter to complete the task of the line inspection,which largely reflects the intelligence and security of the aircraft.Therefore,this paper studies the automatic obstacle avoidance of the quadcopter in power line inspection system.System requirements of the quadcopter used in power line inspection are analyzed.According to the system requirements,the design of the overall scheme of the quadcopter obstacle avoidance platform is completed.The quadcopter obstacle avoidance platform is divided into five subsystems,and the emphasis is put on the analysis of the automatic obstacle avoidance system.The environmental map of the power line is pre processed,including setting up the avoidance boundary line and avoidance cylinder of obstacles.Then grid model of the pretreated environment map is made and expansion treatment of the grid model is carried out.Aiming at the problem that search area of traditional A star algorithm is too large to search path efficiently,an improved A star algorithm is proposed.Distance information and direction information are introduced into the evaluation function,and the direction information is processed into a perturbation to avoid the A star algorithm to search the same cost path.At the same time,the area of the grid map is reduced by using the subregional path search method to improve the running speed of the A star algorithm.The improved A star algorithm is applied to the path planning of the power line inspection,and the path of searching is optimized.The simulation results show that the path searched by the improved A star algorithm is the global optimal path,the search area obviously becomes smaller,and the number of the path nodes is significantly reduced after optimization.The improved A star algorithm for obstacle avoidance planning can not take the dynamic or unknown obstacles into account.In order to solve this problem,a behavior-based control structure is adopted,which contains path tracking behavior and autonomous obstacle avoidance behavior.Task planning module is added to the control structure to plan the overall line inspection task,and line inspection sub tasks are completed by the two kinds of behaviors.The path tracking behavior uses tracking fuzzy controller to track line inspection path which the improved A star algorithm has been well planned,and the autonomous obstacle avoidance behavior selects obstacle avoidance fuzzy controller to avoid the unknown obstacles in real time.Arbitrator is designed to coordinate and integrate the two kinds of behaviors.The historical information of the distance between the aircraft and the obstacle is used as a reference factor for the behavior arbitration,which improves the smoothness of the output of the arbitrator.Simulation results verify that the behavior-based obstacle avoidance control can not only enable the aircraft to fly along the best line inspection route,but also let the aircraft avoid unknown obstacles that appears on the route in real time,which embodies the superiority of the proposed scheme. |
