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- | + | **ANR JCJC project contact: [[https:// | |
- | **ANR JCJC project contact: [[https:// | + | |
**Duration: | **Duration: | ||
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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. | 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. | ||
- | ** 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. |