Title :
AGV decision making subsystem based on modified Dempster-Shafer evidence theory and fuzzy logic
Author :
Liu, Yuqiang ; Huang, Wu-Ling ; Sun, Tao ; Zhu, Fenghua
Author_Institution :
State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China
Abstract :
The AGV decision making subsystem directly affects the performance of the vehicle. The information it uses can be classified into “Objective Information” and “Subjective Information” two major groups. To fuse these two kinds of information, we propose a novel framework for decision in this paper. In the framework, an effective method based on the modified Dempster-Shafer evidence theory was used to make the fusion of the objective and subjective information. In addition, we used fuzzy logic to quantify the subjective information. The experiment shows the proposed method can solve the vagueness and uncertainty of information and achieve decision exactly and credibly.
Keywords :
case-based reasoning; decision making; fuzzy logic; mobile robots; pattern classification; road vehicles; sensor fusion; uncertainty handling; AGV decision making subsystem; autonomous ground vehicle; fuzzy logic; information classification; information uncertainty; modified Dempster-Shafer evidence theory; objective information fusion; subjective information fusion; vehicle performance; Cameras; Cognition; Decision making; Fuses; Fuzzy logic; Sensors;
Conference_Titel :
Vehicular Electronics and Safety (ICVES), 2012 IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-0992-9
DOI :
10.1109/ICVES.2012.6294284