http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Sima Vosoghi Asl,Zohreh Davarzani,Soheila Staji 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11
This article examines navigation of a flying robot inside a building environment in three dimensional spaces in which the size and location of some obstacles are not determined and other obstacles and target can be moving. This article suggests a new method by combining Q-learning algorithm and Monte Carlo algorithm on optimal navigation by the flying robot. The rewards are intended to be maximized when the robot flies in the right route; moreover, the maximum performance power would be measured according to the future predictions and the well-doing of that action would be also measured. Here, this method has been implemented with Webots simulator, and simulated data are analyzed by MATLAB. The simulation results show that control of the policy obtained from Q-learning and Monte Carlo methods is more efficient compared to traditional methods in controlling flying robot navigation.