A New Computational Framework for Efficient Parallelization and Optimization of Large Scale Graph Matching

There are so many applications in data fusion, comparison, and recognition that require a robust and efficient algorithm to match features of multiple images. To improve accuracy and get a more stable result is important to take into consideration both local appearance and the pairwise relationship of features. Graphs are a powerful and flexible data structure, allowing for the description of complex relationships between data elements, whose nodes correspond to salient features and edges correspond to relational aspects between features. Therefore, the problem of graph matching is to find a mapping between the two sets of nodes that preserves the relationships between them as much as possible. This graph-matching problem is mathematically formulated as an IQP problem which solving it is NP-hard, and obtaining exact Optima only plausible for very small data. Therefore, handling large-scale scientific visual data is quite limited, necessitating both efficient serial algorithms, as well as scalable parallel formulations. In this thesis, we first focused on exploring techniques to reduce the computation cost as well as memory usage of Pairwise graph matching by adopting a heuristic pruning strategy together with a redundancy pattern suppression scheme. We also modified the structure of the affinity matrix for minimizing memory requirement and parallelizing our algorithm by employing CPU’s and GPU’s accelerated libraries. Any pair of features with similar distance from first image results in same sub-matrices, therefore instead of constructing the whole affinity matrix, we only built the sub-blocked affinity for those distinct feature distances. By employing this scheme not only saved large memory and reduced computation time tremendously but also, the matrix-vector multiplication of gradient computation performed in parallel, where each block-vector calculation computed independently without synchronization. The accelerated libraries such as MKL, cuSparse, cuBlas and thrust applied to solving the GM problem, following the scheme of the spectral matching algorithm. We also extended our work for Multi-graph imaging, since many tasks require finding correspondences across multiple images. Also, considering more graph improves the matching accuracy. Most algorithms obtain approximate solutions for solving the GM NP-hard problem, result in a weak optimal solution. Therefore, we proposed a new solver, which iteratively modified the affinity matrix and binarized the solution by optimizing the original problem with its integer constraints

A multi-frame graph matching algorithm for low-bandwidth RGB-D SLAM

This paper presents a novel multi-frame graph matching algorithm for reliable partial alignments among point clouds. We use this algorithm to stitch frames for 3D environment reconstruction. The idea is to utilize both descriptor similarity and mutual spatial coherency of features existed in multiple frames to match these frames. The proposed multi-frame matching algorithm can extract coarse correspondence among multiple point clouds more reliably than pairwise matching algorithms, especially when the data are noisy and the overlap is relatively small. When there are insufficient consistent features that appeared in all these frames, our algorithm reduces the number of frames to match to deal with it adaptively. Hence, it is particularly suitable for cost-efficient robotic Simultaneous Localization and Mapping (SLAM). We design a prototype system integrating our matching and reconstruction algorithm on a remotely controlled navigation iRobot, equipped with a Kinect and a Raspberry Pi. Our reconstruction experiments demonstrate the effectiveness of our algorithm and design

Conception, analyse et optimisation de méthodes de préhension et de mains mécaniques épicycloïdales pour la prise d'objets plats partiellement contraints

Dans les applications robotiques, la plupart des préhenseurs sont plus apparentés à des outils qui sont spécialisés pour effectuer une tâche extrêmement bien plutôt que d’effectuer une variété de tâches et de simplement les réussir. C’est dans cette optique que les travaux rapportés dans cette thèse proposent des solutions de préhension. Premièrement, des méthodes générales sont proposées pour permettre de prendre un type d’objets qui est généralement impossible à prendre pour les préhenseurs simples. Par la suite sont présentés les mécanismes planétaires qui sont au cœur des assemblages subséquents. Ces mécanismes sont utilisés pour améliorer les débattements des doigts et ainsi rendent possible un premier design pouvant prendre des petits et grands objets reposant sur des surfaces dures. Par la suite est présenté la conception d’un préhenseur complet qui inclut les propriétés du premier préhenseur mais aussi des propriétés de prises parallèles qui sont considérées comme indispensables pour être en mesure de saisir une grande panoplie d’objets. Finalement, le design du préhenseur proposé est optimisé et des capteurs y sont intégrés pour tenter de produire un design complet et sécuritaire pouvant être utilisé de manière simple par une grande panoplie de robots.Most robotic grippers excel at completing one task but are ill suited for completing many and very different tasks. It is with this fact in mind that this thesis proposes general solutions to the grasping problem. First, general methods are proposed that aim at picking small flat objects that could not otherwise be grasped by simple mechanical grippers. Planetary mechanisms are then proposed to increase the range of motion of the finger joints, hence providing a way to achieve the necessary properties to build and test a finger capable of grasping small flat objects lying on hard surfaces. A complete gripper design is then proposed and built. The novel design that includes the features of the previous design is also capable of performing parallel grasps which are considered essential to be able to grasp a wide range of unknown objects. Finally, the gripper design is optimised and sensing apparatus is included in the gripper to provide a gripper that is considered a complete solution to grasping and is simple to use on a wide range of robots