Research On Autonomous Navigation Control Of USA Considering Real-time Obstacle Avoidance

The Unmanned Surface Vehicle(USV)is a multipurpose marine surface unmanned vehicle,which belongs to the multi-domain unmanned system.The main characteristics of multi-domain unmanned system are reflected in multi-domain and unmanned.Multi-domain refers to the joint sea,land,and air domains,while unmanned emphasizes the autonomy of the single-domain system and the autonomy of the joint system.The autonomy of USV is improved continually to meet the needs of all aspects of the system.Autonomous navigation is the core capability of the autonomy of USV.However,due to the complex and changeable sea surface environment,there are problems such as poor real-time trajectory tracking control accuracy,low security of global path planning,and insufficient adaptability of local obstacle avoidance decision-making planning.So how to realize real-time obstacle avoidance for autonomous navigation of USV has become an urgent problem.Aiming at changes in ocean currents and environmental disturbances,the threedegree-of-freedom mathematical model of USV autonomous navigation is established.On this basis,the adaptive estimation law for ocean currents is designed to estimate changes in ocean currents.Meanwhile,the finite-time disturbance observer is built to observe environmental disturbances.And the controller of the port-controlled Hamilton is constructed to compensation them.Finally,the highprecision and real-time trajectory tracking of the surface unmanned vehicle is achieved.The input of high-precision trajectory tracking is the safe smooth path,and the basic requirement of the safe smooth path is to avoid static and dynamic obstacles on the sea surface.At the same time,the main function of global path planning is to avoid static obstacles.As one of the algorithms,the artificial potential field algorithm has a safe and smooth planning path,which can meet the requirements of highprecision real-time trajectory tracking,but it has the defect of local minimum.To solve the above problems,firstly,the circular expansion of static obstacles is processed;secondly,the local minimum value is improved,and the rotation angle formula is constructed;finally,the local minimum value of the complex environment is improved,and the virtual repulsion potential field is constructed to avoid the local minimum value.The main function of local obstacle avoidance decision planning is to avoid dynamic obstacles.First,the dynamic collision risk model of two ships is established to increase the adaptability,and accurately identify the situation in real time according to the information of the encountering ships and the international regulations for preventing collisions at sea;secondly,the virtual circular repulsion potential field is designed in the outer circular ship area to guide USV to evade smoothly.The velocity ellipse repulsion potential field is constructed in the inner ellipse ship domain to improve the path safety in emergency situations.The trajectory tracking,global path planning and local obstacle avoidance decision planning are studied.The marine environment is combined with the realtime obstacle avoidance characteristics of autonomous navigation,and the above targeted improvement is proposed based on the existing algorithm.After simulations and theoretical analysis,the feasibility and effectiveness of the improved algorithms proposed are verified,and compared with the relevant literature algorithms,the superiority of the proposed improved algorithm is proved,and finally autonomous navigation of the USV for real-time obstacle avoidance in the marine environment is realized.