Conception et commande de robots parallèles pour la stabilisation inertielle de dispositifs de visée
Bibliographic record
Abstract
A sighting device is a set of cameras and/or pointing devices mounted on a carrier that is generally in motion with both rotational and translational movements. Used in various environments such as maritime, terrestrial, or aerial, these devices must maintain a stable line of sight despite external disturbances (waves, vibrations, etc.). The stabilization architectures currently used in the defense industry primarily rely on gimbal systems offering two degrees of freedom in orientation: bearing and elevation. To mechanically improve the quality of stabilization, this thesis explores the use of parallel robots for primarily maritime applications. Despite their advantages in terms of degrees of freedom, rigidity, compactness, and precision, their complexity, particularly related to control and singularity management, presents significant challenges. The research is thus focused on two main areas: the certified design of these parallel architectures for inertial stabilization applications and the development of control strategies adapted to these systems. On one hand, the aim is to develop a design-based methodology that certifies the kinematics of a parallel robot based on its application and workspace, while coping with uncertainties inherent in this type of architecture. Such a methodology relies on a relevant combination of symbolic and semi-numerical tools, with the use of interval arithmetic. This methodology is applied in this thesis through the cases of the 3-RPS tripod and the 3-RRR spherical robot. On the other hand, the goal is to secure the control of the robot by ensuring it remains within the previously certified workspace. This is achieved by implementing a joint limitation algorithm, taking into account both the workspace and the properties of the robot's actuators. Finally, the entire design and control methodology is implemented for the spherical parallel robot with coaxial actuators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".