An Object Detection and Identification System for a Mobile Robot Control

The one of the features of mobile robot control is to detect and to identify objects in workspace. Especially, autonomous systems must detect obstacles and then revise actual trajectories according to new conditions. Hence, many solutions and approaches can be found in literature. Different sensors and cameras are used to solve problem by many researchers. Different type sensors usage can affect not only system performance but also operational cost. In this study, single camera based obstacle detection and identification algorithm was developed to control omni-drive mobile robot systems. Objects and obstacles, which are in robot view, are detected and identified their coordinates by using developed algorithms dynamically. Developed algorithm was tested on Festo Robotino mobile robot. Proposed approach offers not only cost efficiency but also short process time

Unmanned Aerial Vehicle Domain: Areas of Research

Unmanned aerial vehicles (UAVs) domain has seen rapid developments in recent years. As the number of UAVs increases and as the missions involving UAVs vary, new research issues surface. An overview of the existing research areas in the UAV domain has been presented including the nature of the work categorised under different groups. These research areas are divided into two main streams: Technological and operational research areas. The research areas in technology are divided into onboard and ground technologies. The research areas in operations are divided into organization level, brigade level, user level, standards and certifications, regulations and legal, moral, and ethical issues. This overview is intended to serve as a starting point for fellow researchers new to the domain, to help researchers in positioning their research, identifying related research areas, and focusing on the right issues.Defence Science Journal, Vol. 65, No. 4, July 2015, pp. 319-329, DOI: http://dx.doi.org/10.14429/dsj.65.863

Comparison of 3D Versus 4D Path Planning for Unmanned Aerial Vehicles

This research compares 3D versus 4D (three spatial dimensions and the time dimension) multi-objective and multi-criteria path-planning for unmanned aerial vehicles in complex dynamic environments. In this study, we empirically analyse the performances of 3D and 4D path planning approaches. Using the empirical data, we show that the 4D approach is superior over the 3D approach especially in complex dynamic environments. The research model consisting of flight objectives and criteria is developed based on interviews with an experienced military UAV pilot and mission planner to establish realism and relevancy in  unmanned aerial vehicle flight planning. Furthermore, this study incorporates one of the most comprehensive set of criteria identified during our literature search. The simulation results clearly show that the 4D path planning approach is able to provide solutions in complex dynamic environments in which the 3D approach could not find a solution

Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte Carlo simulations.NPRP grant 6-070-2-024 from the Qatar National Research Fund (a member of Qatar Foundation)Scopu

Sequential Monte Carlo Samplers For Nonparametric Bayesian Mixture Models

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2012Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2012Bu çalışmanın temel amacı, parametrik olmayan Bayesçi model seçim teknikleri içinde önemli bir yere sahip olan Dirichlet süreci karışım modelleri (DPM) için etkin ardışık Monte Carlo (SMC) örnekleyiciler tasarlamaktır. Tasarlanan algoritmalar, önerilen sınıf güncelleme metotları sayesinde, yeni gelen gözlemlerin ışığında parçacık gezingelerinde değişiklik yaparak gerçek DPM sonsal dağılımına daha iyi bir yaklaşıklık sağlamaktadır. Önerilen metot, DPM sonsal dağılımının çözümünde kullanılan diğer ardışık Monte Carlo örnekleyicileri genelleme özelliğe sahiptir. Tek ve çok boyutlu olasılık dağılımı kestirim problemlerinde yapılan değerlendirmelerde, özellikle sonsal dağılımın izole modlara sahip olduğu koşullarda, önerilen metodun klasik metotlara göre çok daha yüksek doğrulukta sonuca yakınsayabildiği görülmüştür. Ayrıca, manevralı hedeflerin takibinde ortaya atılan en yenilikçi modellerden biri olan değişken oranlı parçacık süzgeçleri (VRPF) tezde ele alınmış ve çoklu model yaklaşımları değişken oranlı modeller ile birleştirilerek, takip başarımını arttıran çoklu model değişken oranlı parçacık süzgeçleri (MM-VRPF) önerilmiştir. Çoklu model yaklaşımının manevralı hedef gezingelerini daha iyi modellediği benzetim sonuçları ile gösterilmiştir.In this thesis, we developed a novel online algorithm for posterior inference in Dirichlet Process Mixture (DPM) models that is based on the sequential Monte Carlo (SMC) samplers framework. The proposed method enables us to design new clustering update schemes, such as updating past trajectories of the particles in light of recent observations, and still ensures convergence to the true DPM posterior distribution asymptotically. Our method generalizes many sequential importance sampling based approaches and provides a computationally efficient improvement to particle filtering that is less prone to getting trapped in isolated modes. Performance has been evaluated in univariate and multivariate infinite Gaussian mixture density estimation problems. It is shown that the proposed algorithm outperforms conventional Monte Carlo approaches in terms of estimation variance and average log-marginal. Moreover, in this thesis we dealt with the maneuvering target tracking problem. We incorporated multiple model approach with the recently introduced variable rate particle filters (VRPF) in order to improve the tracking performance. The proposed variable rate model structure, referred as Multiple Model Variable Rate Particle Filter (MM-VRPF) results in a much more accurate tracking.DoktoraPh

HISTORY URBANISM RESILIENCE VOLUME 03:

The 17th conference (2016, Delft) of the International Planning History Society (IPHS) and its proceedings place presentations from different continents and on varied topics side by side, providing insight into state-of-the art research in the field of planning history and offering a glimpse of new approaches, themes, papers and books to come. VOLUME 03: Change and Responsive Plannin

BEYOND ALL LIMITS : Procedings on International Conference on Sustainability in Architecture, Planning, and Design : 11-12, 13 May 2022

[Italiano]: Il volume raccoglie gli atti della seconda edizione del convegno “BEYOND ALL LIMITS. International Conference on Sustainability in Architecture, Planning, and Design”, tenutosi nei giorni 11 e 12 maggio 2022, presso il Complesso del Belvedere di San Leucio, sede di Officina Vanvitelli. Il convegno è stato promosso e organizzato dal Dipartimento di Architettura e Disegno Industriale dell'Università degli Studi della Campania “Luigi Vanvitelli”, in partnership con la Faculty of Architecture della Çankaya University di Ankara e la Faculty of Engineering della University of Strathclyde di Glasgow. L’obiettivo principale di questo convegno scientifico e multidisciplinare, che ha interessato i campi dell'architettura, della pianificazione e del design, è stato quello di affrontare il tema della sostenibilità all’interno dell'attuale dibattito internazionale scaturito dal New European Bauhaus (NEB)./[English]: This volume collects the Proceedings of the second edition of the conference “BEYOND ALL LIMITS. International Conference on Sustainability in Architecture, Planning, and Design”, held on May 11 and 12, 2022, at the San Leucio Belvedere Complex, home of Officina Vanvitelli. The conference was sponsored and organized by the Department of Architecture and Industrial Design of the University of Campania “Luigi Vanvitelli”, in partnership with the Faculty of Architecture of Çankaya University in Ankara and the Faculty of Engineering of the University of Strathclyde in Glasgow. The main objective of this scientific and multidisciplinary conference, which covered the fields of architecture, planning and design, was to address the issue of sustainability within the current international debate that has arisen from the New European Bauhaus (NEB)