A new coverage path planning algorithm for unmanned surface mapping vehicle based on A-star based searching

This paper investigates the coverage path planning issues and mapping platform construction for unmanned surface mapping vehicle (USMV). An improved BA ∗ ( IBA ∗ ) algorithm is designed from the unit decomposition method and map update method to solve the problem of insufficient continuity and the high-precision environmental modeling. By means of task decomposition and map dynamic updating, the IBA ∗ algorithm overcomes the shortcoming of local optimization of BA ∗ algorithm effectively, and has a significant decrease more than 10% in the path length, 15% in the number of turns, 85% in the unit number and 2% in the coverage. Moreover, the IBA ∗ algorithm has a greater advantage than the Boustrophedon algorithm and the PPCPP algorithm. Results of simulations and the mapping experiments verify the excellent performance of our IBA ∗ .