Characterizing the Effect of Reduced Gravity on Rover Wheel-Soil \nInteractions
Notice bibliographique
Résumé
The entrapment of the Mars Exploration Rover Spirit in soft regolith and the tears and punctures in the Mars Science Laboratory Curiosity rover’s wheels demonstrate some of the current mobility challenges in granular terrains on extraterrestrial planetary surfaces. \n \nClassical wheel-terrain interaction models used in the literature are unable to sufficiently predict the effects of reduced-gravity on rover performance. Several researchers today highlight the insufficient predictive power of classical terramechanics models for planetary rovers, thus implying a need to renew the experimental underpinnings of our theories. Only a single dataset has been reported in the literature for wheels driving in soil during reduced-g flights, and the actual data collected is limited. This thesis presents data that more than doubles the number of existing reduced-g wheel-soil interaction experiments for the study of terramechanics. One of the key contributions is that it includes the measurement of drawbar pull (i.e. net traction force) data as well as direct observation of wheel-soil interactions (through a glass sidewall), both for the first time ever in reduced gravity. \n \nThe experimentation campaign is designed to inform the upcoming ExoMars space mission, through the use of ExoMars wheel prototype and Martian soil simulant in simulated Martian gravity produced in parabolic flights. An advanced automated gantry system is developed to support this activity with improved control and repeatability over the prior published experiments. In addition to Martian gravity, wheel-soil interactions are also studied in Lunar gravity, all achieved aboard Canada’s National Research Council’s (NRC) Falcon 20 aircraft. Wheel rotation rate, horizontal advance rate, and vertical wheel loading are controlled independently. To address the constraints imposed by testing aboard an aircraft performing parabolic flights and to achieve experimental repeatability and consistency, a novel rapid automated soil preparation subsystem is developed. The consistency and repeatability of the soil preparation are studied and verified both through cone penetration tests and through examining triplicates of terramechanics (i.e. traction force, wheel sinkage) datasets. \n \nA key observation from the terramechanics dataset is a significant reduction of traction (over 30\\% less) in partial gravity experiments (PGE) compared to on-ground experiments (OGE), at the same wheel loading. The complementary visualization analysis results indicate that, with wheel normal load held equal between experiments, the amount of soil mobilized by wheel-soil interaction substantially increases as gravity decreases. The results of the visualization analysis suggest a deterioration in the soil strength at lower gravities, which thus undermines the rover mobility by reducing the net traction. The results have important implications regarding the practice of using a reduced-mass rover on Earth to assess the performance of a full-mass rover in similar soil on a reduced-gravity surface. Other details discovered in the dataset are also further elaborated in this study. \n \nThe analysis of terramechanics data and high-speed images that are collected at Lunar and Martian gravities, and contrasted against OGE, not only guide the understanding of the influence of gravity on wheel performance but also holds promise to fill the gaps of research in the literature. The congruity of analysis of computer vision/clustering techniques with terramechanics results in this campaign highlights a promising technique for studying these interactions in a planetary context. The richness of the data produced, unprecedented in the study of robot-terrain interactions, can highlight gaps and discrepancies in existing models and enables validation of new models that approach robot-terrain interactions with an appropriate and efficient level of detail.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».