Applications of highly accurate localization and navigation to mobile robot

The optimal route planning is to seek the most appropriate path for robot to arrive the desired destination smoothly in the shortest time. In this paper, the Tangent method is firstly used to find the shortest moving route. Secondly, the Kalman filtering algorithm is employed to amend the route errors at the k^th time during the moving status. Simultaneously, the route for next (k + 1)^th time can be also estimated. Finally, the robot route is continuously adjusted using the fuzzy logic controller for the robot moving more smoothly and efficiently. Both simulation and experimental results confirm that the robot can reach the destination fast within no exceeding ±2 cm localization error.