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文章基本信息

  • 标题:State Estimation for Robots with Complementary Redundant Sensors
  • 作者:Daniele Carnevale ; Francesco Martinelli
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2015
  • 卷号:12
  • 期号:10
  • 页码:138
  • DOI:10.5772/60528
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:In this paper, robots equipped with two complementary typologies of redundant sensors are considered: one typology provides sharp measures of some geometrical entity related to the robot pose (e.g., distance or angle) but is not univocally associated with this quantity; the other typology is univocal but is characterized by a low level of precision. A technique is proposed to properly combine these two kinds of measurement both in a stochastic and in a deterministic context. This framework may occur in robotics, for example, when the distance from a known landmark is detected by two different sensors, one based on the signal strength or time of flight of the signal, while the other one measures the phase-shift of the signal, which has a sharp but periodical dependence on the robot-landmark distance. In the stochastic case, an effective solution is a two-stage extended Kalman filter (EKF) which exploits the precise periodic signal only when the estimate of the robot position is sufficiently precise. In the deterministic setting, an approach based on a switching hybrid observer is proposed, and results are analyzed via simulation examples.
  • 关键词:Redundant Sensors; Kalman Filtering; Robot Localization; Observer for Nonlinear Systems
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