Modified Shuffled Frog Leaping Algorithm based 6DOF Motion for Underwater Mobile Robot

Optimal path in an environment containing obstacles for underwater vehicle can be computed using a numerical solution of the nonlinear optimal control problem (NOCP). The underwater vehicle is modelled with six-dimensional nonlinear and coupled equations of motion, controlled by DC motors in all degrees of freedom. The intent of this computation is to offer a comprehensive perception of the behaviour of underwater autonomous vehicle and also to obtain the unknown parameters of the model which can be devoted in motion planning strategy of underwater robot. To execute tasks along a distinctive path in a convoluted environment, motion planning necessities to concede the underwater robot to be in motion between its current and final configurations without any collision within the encircling environment. Traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. The optimization of path as well as time taken has been analysed here using modified shuffled frog leaping (SFL) optimization algorithm based on perception, cognition and sensor fusion. Path scheduling has to be executed for achieving integration of different preliminary robotic behaviours (e.g. obstacle avoidance, wall and edge following, escaping dead end and target seeking) in partially unknown territory (land or water). The optimal path is generated with this method when the robot reaches its target. The simulation studies ensure that the heuristic navigational approach possesses intelligent decision-making capabilities in negotiating hazardous terrain conditions during the under-water robot motion.