Underactuated unmanned ship obstacle avoidance path planning and control method and system

Abstract

The invention provides an underactuated unmanned ship obstacle avoidance path planning and control method and system. The method comprises the steps: the current position of an underactuated unmannedship and the position information of an obstacle in a front fan-shaped area are acquired; based on a potential field analysis method, potential field analysis is carried out on the obtained current position of the under-actuated unmanned ship and the position information of the obstacle in the front fan-shaped area, and the estimation point direction with the minimum resultant potential field is selected as a potential field heading angle; the deviation angle between the potential field heading angle and the current heading angle of the underactuated unmanned surface vehicle and the current position repulsion ratio of the underactuated unmanned surface vehicle are introduced into a designed fuzzy logic controller as two input quantities, and the obstacle avoidance heading angle of the underactuated unmanned surface vehicle in the next step of movement is obtained; and a motion controller is designed and tracking control is carried out on the obstacle avoidance heading angle and the advancing speed to realize collision-free navigation of the under-actuated unmanned ship to a target point. The method has the advantages of being high in calculation speed, high in real-time performance, low in cost and the like.

Description

technical field [0001] The present invention relates to the technical field of unmanned underwater vehicles, in particular, to an underactuated unmanned vehicle obstacle avoidance path planning and control method and system. Background technique [0002] The obstacle avoidance path planning and control system of underactuated UAV is divided into two sub-strategies: obstacle avoidance and control. In terms of obstacle avoidance, the underactuated unmanned boat adopts the traditional artificial potential field obstacle avoidance strategy: abstract the unknown sea area where the unmanned boat is located into a force field, and use the target point of navigation as a gravitational pole to form a gravitational potential field. The encountered sea obstacles act as repulsive poles and generate a repulsive potential field, so that the artificial abstraction of the sea area becomes an artificial potential field composed of the superposition of the two. Perform evasion and drive to t...

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Problems solved by technology

[0004] 1. Since the gravitational potential field function and the repulsive potential field function defined by the traditional artificial potential field obstacle avoidance algorithm are relatively simple, it does not consider the situation that the obstacle is on the line between the unmanned ship and the target point or there is an obstacle near the target point, so it will There are local minimum problems and target unreachable problems, resulting in the unmanned boats being unable to avoid obstacles and reach the target point

Generally, the method of setting virtual guide points, random search or walking along the wall is used to solve the local minimum problem, and the repulsive potential field function that introduces the distance between the unmanned vehicle and the target point is used to solve the problem of unreachable targets. There are few studies on the obstacle distribution problem, and the inherent problems of the traditional artificial potential field method have not been fundamentally solved

[0005] 2. The obstacle avoidance algorithm based on the artificial potential field generally uses the direction of the resultant force composed of attraction and repulsion as the heading of the unmanned boat. When the unmanned boat enters or leaves the area affected by obstacles, the direction of the resultant force will be the resultant force at the previous moment. The direction produces a large angle, but due to the influence of the slewing performance, the slewing angular velocity of the underactuated unmanned vehicle is greatly constrained, which may make the unmanned vehicle unable to quickly follow the planned obstacle avoidance path, making its actual track and plan The path deviation is large, which may cause collisions in serious cases

[0006] 3. The artificial potential field method does not consider the current factors enough, and ignores the influence of the external wind, wave and current interference on the obstacle avoidance accuracy of the unmanned vehicle, which makes the algorithm have great limitations in practical applications.

Some existing studies only adjust the potential field function for the steady ocean current, and it is very difficult to adjust the obstacle avoidance path by considering the influence of the time-varying ocean current through the potential field method

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