SUBSEA VEHICLE PATH PLANNING USING NONLINEAR-PROGRAMMING AND CONSTRUCTIVE SOLID GEOMETRY

It is important to find a collision-free path for an unmanned underwat er vehicle (UUV) and manipulator, from an initial to a goal configurat ion, when considering automated vehicle activity in and around subsea structures. The problem is particularly acute when the combined motion of a vehicle and manipulator is considered, due to large numbers of d egrees of freedom (DOF) which produce a large search space, the need f or an efficient search algorithm, the need for defining cost functions without local minima, and an efficient representation of object geome tries to avoid collisions. Over the past 20 years, a great deal of int erest and progress has developed in robot path planning. This paper co ncentrates on efficient searching and object representation, while rem oving local minima. A novel approach to subsea vehicle/manipulator pat h planning using a nonlinear programming approach is presented. The ce ntral idea is to represent the free space of the workspace as a set of inequality constraints of a nonlinear programming problem, using the vehicle configuration variables. The goal configuration is designed as the unique global minimum point of the objective function. The initia l configuration is treated as the start point for the nonlinear search . Then the numerical algorithm developed for solving the nonlinear pro gramming problem is applied to solve the robot motion planning problem . Every immediate point generated using the nonlinear optimisation sea rch method guarantees that it is in the free space and, therefore, is collision free. Mathematical foundations for constructive solid geomet ry, Boolean operations and approximation techniques are developed and are used to represent the free space of the robot workspace as a set o f inequalities. The advantages of this approach are that mature techni ques developed in the past thirty years, in nonlinear programming theo ry for the direction of search which guarantees convergence, efficienc y and numerical robustness, can be applied directly to the robot path- planning problem. Simulation results show its effectiveness, efficienc y and its potential as an online motion planner.