3,310 research outputs found
A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones
Fully-autonomous miniaturized robots (e.g., drones), with artificial
intelligence (AI) based visual navigation capabilities are extremely
challenging drivers of Internet-of-Things edge intelligence capabilities.
Visual navigation based on AI approaches, such as deep neural networks (DNNs)
are becoming pervasive for standard-size drones, but are considered out of
reach for nanodrones with size of a few cm. In this work, we
present the first (to the best of our knowledge) demonstration of a navigation
engine for autonomous nano-drones capable of closed-loop end-to-end DNN-based
visual navigation. To achieve this goal we developed a complete methodology for
parallel execution of complex DNNs directly on-bard of resource-constrained
milliwatt-scale nodes. Our system is based on GAP8, a novel parallel
ultra-low-power computing platform, and a 27 g commercial, open-source
CrazyFlie 2.0 nano-quadrotor. As part of our general methodology we discuss the
software mapping techniques that enable the state-of-the-art deep convolutional
neural network presented in [1] to be fully executed on-board within a strict 6
fps real-time constraint with no compromise in terms of flight results, while
all processing is done with only 64 mW on average. Our navigation engine is
flexible and can be used to span a wide performance range: at its peak
performance corner it achieves 18 fps while still consuming on average just
3.5% of the power envelope of the deployed nano-aircraft.Comment: 15 pages, 13 figures, 5 tables, 2 listings, accepted for publication
in the IEEE Internet of Things Journal (IEEE IOTJ
Augmented reality over maps
Dissertação de mestrado integrado em Engenharia InformáticaMaps and Geographic Information System (GIS) play a major role in modern society,
particularly on tourism, navigation and personal guidance. However, providing geographical
information of interest related to individual queries remains a strenuous task. The main
constraints are (1) the several information scales available, (2) the large amount of information
available on each scale, and (3) difficulty in directly infer a meaningful geographical context
from text, pictures, or diagrams that are used by most user-aiding systems. To that extent,
and to overcome the aforementioned difficulties, we develop a solution which allows the
overlap of visual information over the maps being queried — a method commonly referred
to as Augmented Reality (AR).
With that in mind, the object of this dissertation is the research and implementation of a
method for the delivery of visual cartographic information over physical (analogue) and
digital two-dimensional (2D) maps utilizing AR. We review existing state-of-art solutions and
outline their limitations across different use cases. Afterwards, we provide a generic modular
solution for a multitude of real-life applications, to name a few: museums, fairs, expositions,
and public street maps. During the development phase, we take into consideration the
trade-off between speed and accuracy in order to develop an accurate and real-time solution.
Finally, we demonstrate the feasibility of our methods with an application on a real use case
based on a map of the city of Oporto, in Portugal.Mapas e Sistema de Informação Geográfica (GIS) desempenham um papel importante na
sociedade, particularmente no turismo, navegação e orientação pessoal. No entanto, fornecer
informações geográficas de interesse a consultas dos utilizadores é uma tarefa árdua. Os
principais dificuldades são (1) as várias escalas de informações disponíveis, (2) a grande
quantidade de informação disponível em cada escala e (3) dificuldade em inferir diretamente
um contexto geográfico significativo a partir dos textos, figuras ou diagramas usados. Assim,
e para superar as dificuldades mencionadas, desenvolvemos uma solução que permite a
sobreposição de informações visuais sobre os mapas que estão a ser consultados - um
método geralmente conhecido como Realidade Aumentada (AR).
Neste sentido, o objetivo desta dissertação é a pesquisa e implementação de um método para
a visualização de informações cartográficas sobre mapas 2D físicos (analógicos) e digitais
utilizando AR. Em primeiro lugar, analisamos o estado da arte juntamente com as soluções
existentes e também as suas limitações nas diversas utilizações possíveis. Posteriormente,
fornecemos uma solução modular genérica para uma várias aplicações reais tais como:
museus, feiras, exposições e mapas públicos de ruas. Durante a fase de desenvolvimento,
tivemos em consideração o compromisso entre velocidade e precisão, a fim de desenvolver
uma solução precisa que funciona em tempo real. Por fim, demonstramos a viabilidade de
nossos métodos com uma aplicação num caso de uso real baseado num mapa da cidade do
Porto (Portugal)
Tile Pattern KL-Divergence for Analysing and Evolving Game Levels
This paper provides a detailed investigation of using the Kullback-Leibler
(KL) Divergence as a way to compare and analyse game-levels, and hence to use
the measure as the objective function of an evolutionary algorithm to evolve
new levels. We describe the benefits of its asymmetry for level analysis and
demonstrate how (not surprisingly) the quality of the results depends on the
features used. Here we use tile-patterns of various sizes as features.
When using the measure for evolution-based level generation, we demonstrate
that the choice of variation operator is critical in order to provide an
efficient search process, and introduce a novel convolutional mutation operator
to facilitate this. We compare the results with alternative generators,
including evolving in the latent space of generative adversarial networks, and
Wave Function Collapse. The results clearly show the proposed method to provide
competitive performance, providing reasonable quality results with very fast
training and reasonably fast generation.Comment: 8 pages plus references. Proceedings of GECCO 201
Quickest Paths in Simulations of Pedestrians
This contribution proposes a method to make agents in a microscopic
simulation of pedestrian traffic walk approximately along a path of estimated
minimal remaining travel time to their destination. Usually models of
pedestrian dynamics are (implicitly) built on the assumption that pedestrians
walk along the shortest path. Model elements formulated to make pedestrians
locally avoid collisions and intrusion into personal space do not produce
motion on quickest paths. Therefore a special model element is needed, if one
wants to model and simulate pedestrians for whom travel time matters most (e.g.
travelers in a station hall who are late for a train). Here such a model
element is proposed, discussed and used within the Social Force Model.Comment: revised version submitte
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