Abstract
In this paper, it is shown how a mobile robot can navigate with high speed in dynamic real environment. Our control scheme is developed based on the dynamic window approach. Although the mobile robot is able to navigate using the DWA, there is a fundamental limitation that the robot can avoid only "visible" obstacles. There are many dangerous regions where dynamic obstacles appear abruptly, in human co-existing real environments. The robot should move "slowly" to prevent unexpected collision in practical application. In order to achieve high speed and safe navigation, a robot should collect environmental information. After collecting sufficient data, a robot navigates in high speed in safe regions. This paper proposes a computational scheme how a robot can distinguish regions of high risk. The proposed scheme is experimentally tested in a real office building. The experimental results clearly show that the proposed scheme is useful for improving a performance of autonomous navigation.
