Research On The Path Planning Method Of Surface Unmanned Vehicle Area Coverage Task

With the rapid development of science and technology,our exploration of the ocean has gradually deepened,and various types of marine robots with different functions have emerged to meet the needs of different tasks.Due to the requirements of environmental monitoring and reconnaissance,terrain detection,anti-mine,anti-submarine and other tasks,unmanned surface vehicle with area coverage technology have gradually become an important research field for marine robots.In this dissertation,a set of complete path planning and tracking control strategies for unmanned surface vehicle are proposed for the area coverage task.There are four aspects of tracking control,and the main contents are as follows:(1)In the practical context of the mission area,the two-dimensional sea surface environment is discretized and the grid map is constructed,so that the environment map can be better combined with the path planning algorithm,and the obstacles are expanded.So the controlled object can be recorded as an abstract point and the safety of the planned path can be guaranteed.(2)For the coverage task path planning requirements,the template model method and the jump point search algorithm are introduced on the basis of the original biological incentive neural network algorithm(BINN)to solve the problem that the BINN algorithm cannot completely cover and is easy to be locked when adjacent to obstacles.In order to meet the task requirements and enrich the functionality of the algorithm,this dissertation introduces an island obstacle,which makes the algorithm give priority to the detection of coverage around the island,and the algorithm also has the ability to preferentially cover the specific task area and solve the problem of obstacle disappearance.After comparing with the BINN algorithm and the A* full coverage path planning algorithm using simulation,it is proved that the improved path planning algorithm in this dissertation improves the efficiency of full coverage path planning,shortens the path length,and reduces the path repetition rate.(3)For the problem that the path planning is not smooth at the turning point,this dissertation introduces the Minimum Snap algorithm to improve the trajectory at the turning point.We also introduce the concept of the safety corridor to solve the problem of the non-ideal optimal path,and adds a guiding function to make the final optimal path smooth and close to the original trajectory.Through the simulation experiment,it is proved that the algorithm in this dissertation can ensure that the unmanned surface vehicle can complete the turning and other movements with the minimum energy consumption under the premise of safe driving.(4)In order to meet the practical requirements under actual sea conditions,a path tracking controller based on model predictive control is designed concerning the drift angle and forward speed,and the ocean current disturbance model is added to verify the robustness of the algorithm.Through the simulation experiment,we find that the unmanned surface vehicle can still accurately complete the coverage task along the established route under the condition of ocean current disturbance.The results fully prove the effectiveness,adaptability and engineering practicability of the path tracking control strategy in this dissertation.After several targeted simulation experiments,it can be proved that the path tracking algorithm,trajectory optimization algorithm and path tracking control algorithm designed on the basis of the environment modeling in this dissertation can make the unmanned surface vehicle complete the area more quickly and efficiently under the premise of ensuring full coverage and with least energy.