Research On Path Planning And Control Method Of Unmanned Vessel Based On ROS

Unmanned Surface Vehicles(USVs)are autonomous vessels capable of navigating and completing various tasks on water.They are increasingly being used in ocean exploration,hydrographic surveying,and environmental monitoring.However,most USVs currently rely on remote control,lacking autonomous navigation and operation capabilities.To address this issue,a set of USV measurement and control system schemes is proposed in this paper,with an in-depth study of the measurement and control system of USVs.Additionally,a USV full-coverage path planning control algorithm with traversal characteristics and a point-to-point path planning control algorithm with the shortest path characteristics are designed in this paper.A USV measurement and control system scheme based on the ROS robot operating system is proposed in this paper,which divides the USV system into an embedded system and a remote monitoring and control system.The embedded system is the main part of the USV,using Jetson Nano and Beagle Bone Blue as the main controllers to realize the planning perception and bottom-level control functions.The remote measurement and control system remotely sends commands to the embedded system of the USV and monitors its status through a wireless network.Regarding the path planning control algorithm for USVs,a full-coverage path planning algorithm based on the biological inspired neural network model is proposed in this paper.This algorithm uses coverage priority and turning consumption functions to modify the activity values of neurons and uses heuristic search to solve dead-end problems during the full-coverage process,combining with grid maps to achieve full-coverage path planning for USVs.Furthermore,an improvement of the heuristic function of the A* algorithm,a path point optimization strategy,and an enhancement of the trajectory evaluation function of the DWA algorithm are proposed in this paper,thereby improving the ability of the algorithm to handle local obstacles.Finally,this paper integrates the two improved algorithms and proposes a point-to-point path planning algorithm suitable for USVs,which can achieve fast and safe navigation to the target position without collision.The proposed path planning algorithms are validated through simulation.Based on the USV measurement and control system scheme proposed in this paper,a USV experimental platform is built,and path planning experiments are conducted in two water surface scenarios: a pool and a lake.The experimental results show that the full-coverage path planning algorithm can effectively achieve complete coverage of the USV’s task water area and can use the point-to-point path planning algorithm for safe return.Moreover,the proposed USV measurement and control system scheme based on the ROS robot operating system provides an effective support method for the USV research field.