辨别力
登普斯特-沙弗理论
传感器融合
移动机器人
稳健性(进化)
人工智能
机器人
计算机科学
公制地图
计算机视觉
模块化设计
帧(网络)
数学
度量空间
基因
认识论
操作系统
数学分析
哲学
电信
生物化学
化学
凸度量空间
出处
期刊:IEEE Transactions on Robotics and Automation
[Institute of Electrical and Electronics Engineers]
日期:1998-04-01
卷期号:14 (2): 197-206
被引量:233
摘要
This article discusses Dempster-Shafer (DS) theory in terms of its utility for sensor fusion for autonomous mobile robots. It exploits two little used components of DS theory: the weight of conflict metric and the enlargement of the frame of discernment. The weight of conflict is used to measure the amount of consensus between different sensors. A lack of consensus leads the robot to either compensate within certain limits or investigate the problem further, adding robustness to the robot's operation. Enlarging the frame of discernment allows a modular decomposition of evidence. This decomposition offers the advantages of perceptual abstraction, and permits expert knowledge about the domain to be embedded in the frames of discernment, simplifying the construction and maintenance of the knowledge base. Six experiments using this Dempster-Shafer framework are presented. Data from four types of sensor data were collected by a mobile robot and fused with the sensor fusion effects (SFX) architecture.
科研通智能强力驱动
Strongly Powered by AbleSci AI