This thesis presents a study on rotation in 2 dimensional and 3 dimensional discrete spaces. In computer science, using floating numbers is problematic due to computation errors. Thus we chose during this thesis to work only in discrete space. In the field of computer vision, the rotation is a transformation required for many applications. Using discretized Euclidean rotation gives bad results. Then, it is necessary to develop new rotation methods adapted to the discrete spaces. We mainly studied the hinge angles that represent the discontinuity of the rotation in the discrete space. Indeed, it is possible to perform two rotations of the same digital image with two angles that are slightly different and obtain the same result. This is captured by hinge angles. Using these angles allow us to describe a discrete rotation that gives the same results than the discretized Euclidean rotation without using floating numbers. They also allow describing an incremental rotation that performs all possible rotations of a given digital image. Using hinge angles can also be extended to the rotations in 3 dimensional discrete spaces. The extension requires the multi-grids that are rotation planes containing three sets of parallel lines. These parallel lines represent the discontinuities of the rotation in 3D discrete space. Thus they are useful to describe the hinge angles in rotation planes. Multi-grids allow obtaining the same results in 3D discrete rotations than the results obtained in 2D discrete rotations. This thesis presents a study on rotation in 2 dimensional and 3 dimensional discrete spaces. In computer science, using floating numbers is problematic due to computation errors. Thus we chose during this thesis to work only in discrete space. In the field of computer vision, the rotation is a transformation required for many applications. Using discretized Euclidean rotation gives bad results. Then, it is necessary to develop new rotation methods adapted to the discrete spaces. We mainly studied the hinge angles that represent the discontinuity of the rotation in the discrete space. Indeed, it is possible to perform two rotations of the same digital image with two angles that are slightly different and obtain the same result. This is captured by hinge angles. Using these angles allow us to describe a discrete rotation that gives the same results than the discretized Euclidean rotation without using floating numbers. They also allow describing an incremental rotation that performs all possible rotations of a given digital image. Using hinge angles can also be extended to the rotations in 3 dimensional discrete spaces. The extension requires the multi-grids that are rotation planes containing three sets of parallel lines. These parallel lines represent the discontinuities of the rotation in 3D discrete space. Thus they are useful to describe the hinge angles in rotation planes. Multi-grids allow obtaining the same results in 3D discrete rotations than the results obtained in 2D discrete rotations

For autonomous mine vehicles that perform the ”load-haul-dump” (LHD) cycle to operate properly, calibration of the sensors they rely on is crucial. The LHD cycle refers to a vehicle that loads material, hauls the material along a route and dumps it in an extraction point. Many of these vehicles are waist-actuated, meaning that the front and rear part of the machines are fixated at an articulation point.   The focus of this thesis is about developing and implementing two differ- ent frameworks to distinguish patterns from routes where calibration of the hinge-angle sensor was needed before and try to predict when calibrating the sensor is needed. We present comparative results of one method using ma- chine learning, specifically supervised learning with support vector machine and one optimization-based method using scan matching by implementing a two-dimensional NDT (Normal Distributions Transform) algorithm.   Comparative results based on evaluation metrics used in this thesis show that detecting incorrect behaviour of the hinge-angle sensor is possible. Evaluation show that the machine learning classifier performs better on the data used for this thesis than the optimization-based classifier.

Cette thèse présente une étude sur les rotations dans les espaces discrets en 2 dimensions et en 3 dimensions. Dans le cadre de l'informatique, l'utilisation des nombres flottants n'est pas recommandée du fait des erreurs de calculs que cela implique. Nous avons donc fait le choix de nous concentrer sur les espaces discrets. Dans le domaine de la vision par ordinateur, la rotation est une transformation requise pour de nombreuses applications. L'utilisation de la rotation continue discrétisée donne des résultats de mauvaise qualité. Pour cette raison, il est nécessaire de développer de nouvelles méthodes de rotation adaptées aux espaces discrets. Nous nous sommes principalement intéressés aux angles charnières qui représentent la discontinuité de la rotation dans les espaces discrets. Dans ces espaces, deux rotations d'une image avec deux angles très proches peuvent donner le même résultat, ce qui est capturé par les angles charnières. L'utilisation de ces angles permet de décrire une rotation qui donne les mêmes résultats que la rotation continue discrétisée tout en n'utilisant que des nombres entiers. Ils permettent aussi de définir une rotation incrémentale qui décrit toutes les rotations possibles d'une image digitale donnée. Les angles charnières peuvent être étendus dans les espaces discrets en trois dimensions. Pour cela, on définit les multi-grilles qui sont des plans de rotations contenant trois ensembles de droites parallèles. Elles représentent les discontinuités de la rotation en 3D. Les multi-grilles permettent d'obtenir les mêmes résultats en 3D que ceux obtenus en 2D / This thesis presents a study on rotation in 2 dimensional and 3 dimensional discrete spaces. In computer science, using floating numbers is problematic due to computation errors. Thus we chose during this thesis to work only in discrete space. In the field of computer vision, the rotation is a transformation required for many applications. Using discretized Euclidean rotation gives bad results. Then, it is necessary to develop new rotation methods adapted to the discrete spaces. We mainly studied the hinge angles that represent the discontinuity of the rotation in the discrete space. Indeed, it is possible to perform two rotations of the same digital image with two angles that are slightly different and obtain the same result. This is captured by hinge angles. Using these angles allow us to describe a discrete rotation that gives the same results than the discretized Euclidean rotation without using floating numbers. They also allow describing an incremental rotation that performs all possible rotations of a given digital image. Using hinge angles can also be extended to the rotations in 3 dimensional discrete spaces. The extension requires the multi-grids that are rotation planes containing three sets of parallel lines. These parallel lines represent the discontinuities of the rotation in 3D discrete space. Thus they are useful to describe the hinge angles in rotation planes. Multi-grids allow obtaining the same results in 3D discrete rotations than the results obtained in 2D discrete rotations. This thesis presents a study on rotation in 2 dimensional and 3 dimensional discrete spaces. In computer science, using floating numbers is problematic due to computation errors. Thus we chose during this thesis to work only in discrete space. In the field of computer vision, the rotation is a transformation required for many applications. Using discretized Euclidean rotation gives bad results. Then, it is necessary to develop new rotation methods adapted to the discrete spaces. We mainly studied the hinge angles that represent the discontinuity of the rotation in the discrete space. Indeed, it is possible to perform two rotations of the same digital image with two angles that are slightly different and obtain the same result. This is captured by hinge angles. Using these angles allow us to describe a discrete rotation that gives the same results than the discretized Euclidean rotation without using floating numbers. They also allow describing an incremental rotation that performs all possible rotations of a given digital image. Using hinge angles can also be extended to the rotations in 3 dimensional discrete spaces. The extension requires the multi-grids that are rotation planes containing three sets of parallel lines. These parallel lines represent the discontinuities of the rotation in 3D discrete space. Thus they are useful to describe the hinge angles in rotation planes. Multi-grids allow obtaining the same results in 3D discrete rotations than the results obtained in 2D discrete rotations