Reducing Communication Delay Variability for a Group of Robots

A novel architecture is presented for reducing communication delay variability for a group of robots. This architecture relies on using three components: a microprocessor architecture that allows deterministic real-time tasks; an event-based communication protocol in which nodes transmit in a TDMA fashion, without the need of global clock synchronization techniques; and a novel communication scheme that enables deterministic communications by allowing senders to transmit without regard for the state of the medium or coordination with other senders, and receivers can tease apart messages sent simultaneously with a high probability of success. This approach compared to others, allows simultaneous communications without regard for the state of the transmission medium, it allows deterministic communications, and it enables ordered communications that can be a applied in a team of robots. Simulations and experimental results are also included

Towards a cloud‑based automated surveillance system using wireless technologies

Cloud Computing can bring multiple benefits for Smart Cities. It permits the easy creation of centralized knowledge bases, thus straightforwardly enabling that multiple embedded systems (such as sensor or control devices) can have a collaborative, shared intelligence. In addition to this, thanks to its vast computing power, complex tasks can be done over low-spec devices just by offloading computation to the cloud, with the additional advantage of saving energy. In this work, cloud’s capabilities are exploited to implement and test a cloud-based surveillance system. Using a shared, 3D symbolic world model, different devices have a complete knowledge of all the elements, people and intruders in a certain open area or inside a building. The implementation of a volumetric, 3D, object-oriented, cloud-based world model (including semantic information) is novel as far as we know. Very simple devices (orange Pi) can send RGBD streams (using kinect cameras) to the cloud, where all the processing is distributed and done thanks to its inherent scalability. A proof-of-concept experiment is done in this paper in a testing lab with multiple cameras connected to the cloud with 802.11ac wireless technology. Our results show that this kind of surveillance system is possible currently, and that trends indicate that it can be improved at a short term to produce high performance vigilance system using low-speed devices. In addition, this proof-of-concept claims that many interesting opportunities and challenges arise, for example, when mobile watch robots and fixed cameras would act as a team for carrying out complex collaborative surveillance strategies.Ministerio de Economía y Competitividad TEC2016-77785-PJunta de Andalucía P12-TIC-130

Estudio y evaluación de plataformas de distribución de cómputo intensivo sobre sistemas externos para sistemas empotrados.

Falta palabras claveNowadays, the capabilities of current embedded systems are constantly increasing, having a wide range of applications. However, there are a plethora of intensive computing tasks that, because of their hardware limitations, are unable to perform successfully. Moreover, there are innumerable tasks with strict deadlines to meet (e.g. Real Time Systems). Because of that, the use of external platforms with sufficient computing power is becoming widespread, especially thanks to the advent of Cloud Computing in recent years. Its use for knowledge sharing and information storage has been demonstrated innumerable times in the literature. However, its core properties, such as dynamic scalability, energy efficiency, infinite resources... amongst others, also make it the perfect candidate for computation off-loading. In this sense, this thesis demonstrates this fact in applying Cloud Computing in the area of Robotics (Cloud Robotics). This is done by building a 3D Point Cloud Extraction Platform, where robots can offload the complex stereo vision task of obtaining a 3D Point Cloud (3DPC) from Stereo Frames. In addition to this, the platform was applied to a typical robotics application: a Navigation Assistant. Using this case, the core challenges of computation offloading were thoroughly analyzed: the role of communication technologies (with special focus on 802.11ac), the role of offloading models, how to overcome the problem of communication delays by using predictive time corrections, until what extent offloading is a better choice compared to processing on board... etc. Furthermore, real navigation tests were performed, showing that better navigation results are obtained when using computation offloading. This experience was a starting point for the final research of this thesis: an extension of Amdahl’s Law for Cloud Computing. This will provide a better understanding of Computation Offloading’s inherent factors, especially focused on time and energy speedups. In addition to this, it helps to make some predictions regarding the future of Cloud Computing and computation offloading