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Knowledge-driven path planning for mobile robots: relative state tree
Chen Y(陈洋); Cheng L(程磊); Wu HY(吴怀宇); Zhao XG(赵新刚); Han JD(韩建达)
作者部门机器人学研究室
关键词Path Planning Relative State Tree Hierarchical Tree Incremental Learning Autonomous Planning
发表期刊Soft Computing
ISSN1432-7643
2015
卷号19期号:3页码:763-773
收录类别SCI ; EI
EI收录号20143600007187
WOS记录号WOS:000351409400017
产权排序2
摘要Path planning is important in the field of mobile robot. However, traditional path planning techniques optimize the navigation path solely based on the models of the robot and the environments. Owing to the time-varying environment, the robot is expected to launch the replanning procedure in real-time continuously. It is slow and wastes computing resources for repeated decisions. In this study, a new perspective is adopted which utilizes a knowledge-driven approach for path planning. The concept of relative state tree is proposed to develop an incremental learning method based on a path planning knowledge base. The knowledge library, which stores a collection of the mappings from environmental information to robot decisions, can be established by offline or online learnings. As the robot plans online, its movement is guided by the optimal decision that is retrieved from the library based on the information which matches mostly the current environment. A large number of simulations are executed to verify the proposed method. When comparing to $k$-d tree, this novel method has shown to use smaller storage space and have higher efficiency.
语种英语
WOS标题词Science & Technology ; Technology
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications
关键词[WOS]TIME OBSTACLE AVOIDANCE ; ALGORITHM ; OPTIMIZATION
WOS研究方向Computer Science
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/14748
专题机器人学研究室
通讯作者Chen Y(陈洋)
作者单位1.School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
推荐引用方式
GB/T 7714
Chen Y,Cheng L,Wu HY,et al. Knowledge-driven path planning for mobile robots: relative state tree[J]. Soft Computing,2015,19(3):763-773.
APA Chen Y,Cheng L,Wu HY,Zhao XG,&Han JD.(2015).Knowledge-driven path planning for mobile robots: relative state tree.Soft Computing,19(3),763-773.
MLA Chen Y,et al."Knowledge-driven path planning for mobile robots: relative state tree".Soft Computing 19.3(2015):763-773.
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