文献类型：期刊文献

英文题名：A Soar-Based Space Exploration Algorithm for Mobile Robots

作者：Luo, Fei[1];Zhou, Qin[1];Fuentes, Joel[2];Ding, Weichao[1];Gu, Chunhua[1]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai, Peoples R China;[2]Univ Bio Bio, Dept Comp Sci & Informat Technol, Chillan 3780000, Chile

年份：2022

卷号：24

期号：3

外文期刊名：ENTROPY

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000776849700001)】；

基金：This research was funded by the project on the Shanghai Action Plan of Technological Innovation (20DZ1201400, 22ZR1416500) and sponsored by Shanghai Sailing Program (20YF1410900).

语种：英文

外文关键词：space exploration; cognitive computing; Soar; heuristic algorithms; reinforcement learning

摘要：Space exploration is a hot topic in the application field of mobile robots. Proposed solutions have included the frontier exploration algorithm, heuristic algorithms, and deep reinforcement learning. However, these methods cannot solve space exploration in time in a dynamic environment. This paper models the space exploration problem of mobile robots based on the decision-making process of the cognitive architecture of Soar, and three space exploration heuristic algorithms (HAs) are further proposed based on the model to improve the exploration speed of the robot. Experiments are carried out based on the Easter environment, and the results show that HAs have improved the exploration speed of the Easter robot at least 2.04 times of the original algorithm in Easter, verifying the effectiveness of the proposed robot space exploration strategy and the corresponding HAs.