Efficient path evaluation for AUVs using adaptive B-spline approximation

This paper presents an optimal and efficient path planner using adaptive B-spline approximation mechanism for Autonomous Underwater Vehicles (AUVs) operating in turbulent, cluttered and uncertain environments. The proposed method recursively inserts midpoint knots until an approximated B-Spline curve that satisfies the accuracy criteria is achieved. The method is able to adapt the quantity of internal knots inserted based on the specific needs of each path to conform to its respective desired smooth path and satisfy the accuracy criteria. Consequently, this method effectively minimizes the number of internal knots for any given trajectory, thus effectively improving the computation efficiency of the path fitness evaluation and hence path planning. The proposed method is integrated with a Genetic Algorithm (GA) based path planner and tested to generate an optimal trajectory for an AUV travelling through a turbulent ocean field in scenarios with uncertainty in position estimates. Simulation results show that the resulting approach is able to quickly and effectively guide the AUV to its destination with significant savings in computation time compared with B-Spline based planners with fixed numbers of internal nodes.