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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Proportional Integral (PI) controllers are a fundamental component in modern control systems, widely used to enhance performance and mitigate steady-state errors. They are particularly effective in applications such as automatic brightness adjustment on smartphones, where they excel at mitigating steady-state errors for step-function inputs. Unlike PD controllers, which require time-varying errors to function optimally, PI controllers leverage their integral component to address residual...
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Generalized Psychophysiological Interaction PPI Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
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分散状态估计:一种使用伪测量和整合前测量的方法.

Charles Champagne Cossette1, Mohammed Ayman Shalaby1, David Saussié2

  • 1Department of Mechanical Engineering, McGill University, Montreal, QC, Canada.

The International journal of robotics research
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PubMed
概括

本研究引入了机器人团队中去中心化状态估计的伪测量,使得有效的通信和强大的可观测性测试成为可能. 深度自动编码器进一步减少了协作机器人的通信需求.

关键词:
谎言组 谎言组是一个谎言组.估计相对地位的估计.协作本地化的本地化.多机器人系统是多机器人系统.整合前的情况.国家估计估计.

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科学领域:

  • 机器人技术 机器人技术 机器人技术
  • 控制理论 控制理论
  • 分布式系统 分布式系统

背景情况:

  • 分散状态估计对于多机器人系统至关重要.
  • 现有的方法在通信效率和可观测性分析方面面临挑战.
  • 机器人经常需要估计类似的物理量,比如相对位置.

研究的目的:

  • 在机器人团队中开发一种新型的去中心化,协作状态估计框架.
  • 引入伪测量来建模机器人间状态关系.
  • 在多机器人系统中提高通信效率和可观察性测试.

主要方法:

  • 引入了伪测量来建模机器人状态估计之间的关系.
  • 开发了一个通用的可观测性测试,考虑传感器测量和通信结构.
  • 拟议的输入预集成,以实现通信效率高的公里计共享.
  • 使用深度自动编码器重建共变量信息,减少通信开销.
  • 将框架应用于向量空间和李组状态定义.

主要成果:

  • 使用伪测量证明了去中心化状态估计的可处理性.
  • 展示了分散式机器人系统的统一可观测性测试.
  • 验证了输入预集成和基于深度自编码器的协差重建的通信效率.
  • 成功评估了模拟问题的框架和四旋翼飞机实验.

结论:

  • 拟议的伪测量框架为分散的协作状态估计提供了可处理和有效的解决方案.
  • 开发的方法显著提高了机器人团队的通信效率和可观察性分析.
  • 该框架具有多功能性,适用于各种状态定义,并在实际场景中得到验证.