Global dynamic path-planning algorithm in gravity-aided inertial navigation system

Signals from gyros and accelerometers in an inertial navigation system (INS) can be processed to obtain navigation information while its errors accumulate with time. A path with long-term characteristics is more likely to encounter unpredictable dynamic conditions. To deal with such problems, this work improves the global static path-planning algorithm based on the A* algorithm, and the local dynamic path-planning algorithm based on dynamic window approach (DWA). In the global planning algorithm, the gravity index and the heading index are incorporated into the cost function of the A* algorithm to consider the mismatches and the deflection of the path. Furthermore, the search method of the A* algorithm is also improved. In the local planning algorithm, the motion model of the DWA algorithm is improved to a high-precision model and expressed in a geographic coordinate system. Finally, the improved global static planning and local dynamic planning are combined as the global dynamic path-planning algorithm of an underwater vehicle. The simulation results show that the global dynamic path-planning algorithm proposed can realise obstacle-free navigation of the underwater vehicle.