Obstacle avoidance strategy based on adaptive potential fields generated by an electronic stick

In our previous work, an obstacle avoidance algorithm, which used potential fields and a similar strategy to that adopted by a blind person to avoid obstacles whilst walking, was proposed. The problem analyzed consists of an AGV (Autonomous Guided Vehicle) which moves within an office environment with a known floor plan and uses an ”electronic stick” made up of infrared sensors to detect unknown obstacles in its path. Initially, a global potential navigation function, defined for each room in the floor plan, incorporates information about the dimensions of the room and the position of the door which the AGV must use to leave the room. Whilst the AGV moves, this global potential navigation function is properly modified to incorporate information about any newly detected obstacle. The main interesting aspect of the proposed approach is that the potential function adaptation involves very low computational burden allowing for the use of Ultra-fast AGVs. Other distinctive features of the algorithm are that it is free from local minima, the obstacles can have any shape, low cost sensors can be used to detect obstacles and an appropriate balance is achieved between the use of the global and the local approaches for collision avoidance. Our present work is a refinement of this strategy that allows for an automatic real time adaptation of the algorithm’s parameters. Now, the algorithm’s functioning requires only that the minimum distance at which the AGV can approach an obstacle (i.e. the closest it can get to any obstacle) is defined a priori. Aspects of the real implementation of the algorithm are also discussed

Application of a blind person strategy for obstacle avoidance with the use of potential fields

This paper proposes a new obstacle avoidance algorithm for the CONTROLAB AGV which uses a similar strategy adopted by a blind person to avoid obstacles while walking. The AGV moves within an office environment with a known floorplan and uses an "electronic stick" consisting of infraredsensors to detect unknown obstacles. Initially a global potential field function is defined for each floorplan room. While the AGV is moving, the original potential function is modified each time an obstacle is detected by the infrared sensors. This modification is simply performed by the addition of previously calculated potentlal field values on a grid which represents the room working area. The interestlng aspects of the proposed approach are that the potential function adaptation involves very low computational burden, the algorithm is free from local minima, the obstacles can have any shape and low cost sensors can be used to detect obstacles

Curvas e superfícies

Este trabalho apresenta uma exposição dos conceitos teóricos da computação gráfica referente às curvas e superfícies. Inicialmente é feita uma apresentação da conceituação de curvas e superfícies da geometria e da geometria diferencial e em seguida discute-se a adaptação destes conceitos às necessidades da computação gráfica. Mais precisamente, são apresentadas as diversas formas de representação das curvas e superfícies como curvas e superfícies paramétricas polinomiais por partes

CONTROLAB MUFA: a multi-level fusion architecture for intelligent navigation of a telerobot

This paper proposes a MUlti-level Fusion Architecture (MUFA) for controlling the navigation of a tele-commanded Autonomous Guided Vehicle (AGV). The architecture combines ideas derived from the fundamental concepts of sensor fusion and distributed intelligence. The focus of the work is the development of an intelligent navigation system for a tricycle drive AGV with the ability to move autonomously within any office enviromnent, following instructions issued by client stations connected to the office network and reacting accordingly to different situations found in the real world. The modules which integrate the MUFA architecture are discussed and results of some simulation experiments are presented

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Braille Fácil: editor de textos para transcrição Braille

O sistema Braille é um código universal tátil para leitura e escrita, usado por pessoas cegas, desenvolvido por Louis Braille, na França, no início do século XIX.  Este sistema é utilizado em diversos idiomas, em textos comuns, e com algumas variações, na simbologia matemática e científica, na música e na informática. Para tornar simples a transcrição computadorizada de Braille, e em particular, atendendo aos requisitos do Governo Brasileiro para o Plano Nacional do Livro Didático em Braille, em 2005 foi criado no NCE/UFRJ (hoje Instituto Tércio Pacitti), em parceria com a ONG Acessibilidade Brasil, o software Braille Fácil, um editor de textos com facilidades específicas, que permite a digitação de textos (ou transcrição com recorte e colagem) e sua impressão quase automática numa impressora Braille. No Braille Fácil, podem ser agregados aos textos digitados alguns códigos de formatação específicos, que permitem ajustes finos com o objetivo de obter uma impressão legível, formatada e muito bem organizada. A interface do programa é muito simples e pouco difere de um editor de textos comum, com a vantagem de que o texto digitado pode ser formatado e visualizado antes da impressão em Braille, com enorme economia de tempo e de gasto de papel. O Braille Fácil é o sistema de transcrição oficial para o sistema Braille usado por instituições de renome, como o Instituto Benjamin Constant, no Brasil, e a Biblioteca Nacional de Portugal. A escolha do Braille Fácil como a melhor opção de impressão de Braille, está diretamente ligada ao fato de que seu uso proporciona enorme velocidade e qualidade de geração de textos. Os recentes desenvolvimentos do sistema, realizados nos últimos meses por nossa equipe, têm proporcionado facilidades tais como a Impressão de Gráficos Táteis, que podem ser embutidos no texto.  Desta forma é possível a transcrição de livros didáticos contemporâneos, em que as figuras são partes essenciais, e que atendem aos conteúdos programáticos das escolas regulares. É possível, então, gerar livros com grande qualidade técnica, atendendo aos requisitos mais elevados de transcrição de materiais textuais para cegos. Concluímos, portanto, ser relevante a divulgação de informações sobre o desenvolvimento deste sistema, hoje utilizado por centenas de escolas em quase todos os países da CPLP (Comunidade de Países de Língua Portuguesa), como forma de garantir o aumento de oportunidades no acesso, formação e inclusão social para os alunos com deficiência visual. Palavras-chave: Tecnologia Assistiva, Deficiência Visual, Braille

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data