Improving Global Motion Planning for Mobile Robots by Experimental Measurement of Travelling Time

This paper describes a new technique for improving global path planning for mobile robots in partially known indoor environments. The method is based on the periodical measurement of the time and position reached by the robot while moving to the goal and on the modification of each branch cost. Due to non-modeled obstacles, there is generally a deviation from the original trajectory calculated using an environment map. Usually, global path planning does not consider this information for new optimal time path search. This approach takes into account statistics about the navigation time when performing different trajectories, avoiding the necessity of dealing with the sensor map information.