ON FPGA BASED ACCELERATION OF IMAGE PROCESSING IN MOBILE ROBOTICS

In visual navigation tasks, a lack of the computational resources is one of the main limitations of micro robotic platforms to be deployed in autonomous missions. It is because the most of nowadays techniques of visual navigation relies on a detection of salient points that is computationally very demanding. In this paper, an FPGA assisted acceleration of image processing is considered to overcome limitations of computational resources available on-board and to enable high processing speeds while it may lower the power consumption of the system. The paper reports on performance evaluation of the CPU–based and FPGA–based implementations of a visual teach-and-repeat navigation system based on detection and tracking of the FAST image salient points. The results indicate that even a computationally efficient FAST algorithm can benefit from a parallel (low–cost) FPGA–based implementation that has a competitive processing time but more importantly it is a more power efficient

Keyframe-based monocular SLAM: design, survey, and future directions

Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality. Although filter-based monocular SLAM systems were common at some time, the more efficient keyframe-based solutions are becoming the de facto methodology for building a monocular SLAM system. The objective of this paper is threefold: first, the paper serves as a guideline for people seeking to design their own monocular SLAM according to specific environmental constraints. Second, it presents a survey that covers the various keyframe-based monocular SLAM systems in the literature, detailing the components of their implementation, and critically assessing the specific strategies made in each proposed solution. Third, the paper provides insight into the direction of future research in this field, to address the major limitations still facing monocular SLAM; namely, in the issues of illumination changes, initialization, highly dynamic motion, poorly textured scenes, repetitive textures, map maintenance, and failure recovery

Mobile Augmented Reality: Applications and Spe-cific Technical Issues

DOI: 10.1007/978-3-319-04702-7 Print ISBN: 978-3-319-04701-0 Online ISBN: 978-3-319-04702-7Although human's sedentary nature over time, his wish to travel the world remains as strong as ever. This paper discusses how imagery and Augmented Reality (AR) techniques can be of great help not only when discovering a new urban environment but also when observ-ing the evolution of the natural environment. The study is applied on Smartphone which is currently our most familiar device. Smart phone is utilized in our daily lives because it is low weight, ease of communications, and other valuable applications. In this chapter, we discuss technical issues of augmented reality especially with building recognition. Our building recog-nition method is based on an efficient hybrid approach, which combines the potentials of Speeded Up Robust Features (SURF) features points and lines. Our method relies on Approxi-mate Nearest Neighbors Search approach (ANNS). Although ANNS approaches are high speed, they are less accurate than linear algorithms. To assure an optimal trade-off between speed and accuracy, the proposed method performs a filtering step on the top of the ANNS. Finally, our method calls Hausdorff measure [15] with line models

Towards high-accuracy augmented reality GIS for architecture and geo-engineering

L’architecture et la géo-ingénierie sont des domaines où les professionnels doivent prendre des décisions critiques. Ceux-ci requièrent des outils de haute précision pour les assister dans leurs tâches quotidiennes. La Réalité Augmentée (RA) présente un excellent potentiel pour ces professionnels en leur permettant de faciliter l’association des plans 2D/3D représentatifs des ouvrages sur lesquels ils doivent intervenir, avec leur perception de ces ouvrages dans la réalité. Les outils de visualisation s’appuyant sur la RA permettent d’effectuer ce recalage entre modélisation spatiale et réalité dans le champ de vue de l’usager. Cependant, ces systèmes de RA nécessitent des solutions de positionnement en temps réel de très haute précision. Ce n’est pas chose facile, spécialement dans les environnements urbains ou sur les sites de construction. Ce projet propose donc d’investiguer les principaux défis que présente un système de RA haute précision basé sur les panoramas omnidirectionels.Architecture and geo-engineering are application domains where professionals need to take critical decisions. These professionals require high-precision tools to assist them in their daily decision taking process. Augmented Reality (AR) shows great potential to allow easier association between the abstract 2D drawings and 3D models representing infrastructure under reviewing and the actual perception of these objects in the reality. The different visualization tools based on AR allow to overlay the virtual models and the reality in the field of view of the user. However, the architecture and geo-engineering context requires high-accuracy and real-time positioning from these AR systems. This is not a trivial task, especially in urban environments or on construction sites where the surroundings may be crowded and highly dynamic. This project investigates the accuracy requirements of mobile AR GIS as well as the main challenges to address when tackling high-accuracy AR based on omnidirectional panoramas