Research on improved RRT* algorithm based on multiple constraints for 3D global path planning
An improved algorithm for rapidly-exploring random tree*(RRT*)algorithm considering multiple con-straints was established to address the slow convergence speed and inability of the planned path to meet the actual naviga-tion constraints of underactuated underwater unmanned vehicles in the process of finding suboptimal paths in three-dimen-sional state space.For the defect of slow optimization process,the improved algorithm accelerates the convergence process of random tree optimization by increasing the probability guidance measures of random tree nodes,increasing the target tendency of tree expansion process,reducing redundant calculations caused by random expansion of tree nodes,and thus ac-celerating the convergence process of random tree optimization;For the navigation constraint problem of unmanned under-water vehicles,the pseudo distance value function between nodes is constructed by combining the pitch and yaw angle con-straints of the vehicle with the Euclidean distance in the original algorithm,so as to further meet the operational laws of un-deractuated underwater unmanned vehicles in the planned path.After Matlab simulation,under the same number of itera-tions in three-dimensional space,the improved algorithm can significantly improve the convergence speed of the optimal path search compared to the traditional RRT*algorithm.The planned path conforms to the motion constraints of underwater unmanned vehicles in terms of pitch and yaw angle changes.
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