UMR CNRS 7253

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en:start [2022/03/01 16:07]
alhagejo 		en:start [2022/03/01 16:10] (current)
alhagejo
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 {{image4.png}} {{image4.png}}
  
-  +**ANR JCJC project contact: [[https://www.hds.utc.fr/~alhagejo/|Joelle Al Hage]]: ** joelle.al-hage[at]hds.utc.fr 
-**ANR JCJC project contact: [[https://www.hds.utc.fr/~alhagejo/|Joelle Al Hage]] ** joelle.al-hage[at]hds.utc.fr +
  
 **Duration:** March 2022-February 2026 **Duration:** March 2022-February 2026
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 The goal of this project is to contribute to the definition of new state estimation methods that overcome simplified assumptions in order to improve the accuracy and the consistency of the estimation output. The contribution of parameter learning strategy (covariance matrix, degrees of freedom, fault detection threshold, fault amplitude) to model-based methods will be investigated in terms of accuracy and integrity. One of our goals is that the learning approach can deal with a partial ground truth.  On the other hand, we want to take advantage of the collaborative framework to improve the accuracy and reduce the uncertainty in the overall system. The integrity of the exchanged information in the system is also an important topic to address. The goal of this project is to contribute to the definition of new state estimation methods that overcome simplified assumptions in order to improve the accuracy and the consistency of the estimation output. The contribution of parameter learning strategy (covariance matrix, degrees of freedom, fault detection threshold, fault amplitude) to model-based methods will be investigated in terms of accuracy and integrity. One of our goals is that the learning approach can deal with a partial ground truth.  On the other hand, we want to take advantage of the collaborative framework to improve the accuracy and reduce the uncertainty in the overall system. The integrity of the exchanged information in the system is also an important topic to address.
  
-** Objective**+** Objectives**
  
 The final objective of ToICar consists in achieving a safe autonomous multi-robot system from the integrity perspective. The final objective of ToICar consists in achieving a safe autonomous multi-robot system from the integrity perspective.
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 The end-results of the project will be the development of methods that will meet two distinct needs: The end-results of the project will be the development of methods that will meet two distinct needs:
   - Offer the possibility to give an accurate and consistent estimation output by exploring the contribution of Artificial Intelligence (AI) to model-based methods and by overcoming simplified assumptions.   - Offer the possibility to give an accurate and consistent estimation output by exploring the contribution of Artificial Intelligence (AI) to model-based methods and by overcoming simplified assumptions.
-  - Ordered List ItemPropose an efficient approach that takes advantage of robot collaboration to deal with sensors faults and to reduce the uncertainty in the overall system. +  - Propose an efficient approach that takes advantage of robot collaboration to deal with sensors faults and to reduce the uncertainty in the overall system. 
  
  
  

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en/start.1646147222.txt.gz · Last modified: 2022/03/01 16:07 by alhagejo
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