Navigation of underwater robot based on dynamically adaptive harmony search algorithm

The current research work has employed an evolutionary based novel navigational strategy to trace the collision free near optimal path for underwater robot in a three-dimensional scenario. The population based harmony search algorithm has been dynamically adapted and used to search next global best pose for underwater robot while obstacle is identified near about robot’s current pose. Each pose is evaluated based on their respective value for objective function which incorporates features of path length minimization as well as obstacle avoidance. Dynamic adaptation of control parameters and new perturbation schemes for solution vectors of harmony search has been proposed to strengthen both exploitation and randomization ability of present search process in a balanced manner. Such adaptive tuning process has found to be more effective for avoiding early convergence during underwater motion in comparison with performances of other popular variants of Harmony Search. The proposed path planning method has also shown better navigational performance in comparison with improved version of ant colony optimization and heuristic potential field method for avoiding static obstacles of different shape and sizes during underwater motion. Simulation studies and corresponding experimental verification for three-dimensional navigation are performed to check the accuracy, robustness and efficiency of proposed dynamically adaptive harmony search algorithm.