Controlo da locomoção e previsão de eficiência de um robô hexápode recorrendo a aprendizagem supervisionada

Dissertação de estrado integrado em Engenharia MecânicaO crescente interesse no campo da robótica móvel tem levado a um aumento na investigação e desenvolvimento de robôs móveis autónomos, especialmente para realizar tarefas perigosas para os seres humanos. Para se deslocarem em ambientes complexos, os robôs hexápodes são uma boa escolha devido à sua capacidade de se adaptarem a diferentes tipos de terreno graças ao seu elevado número de marchas. Além disso, a estabilidade corporal dos robôs hexápodes é considerada uma prioridade para a navegação em ambientes desafiantes. A dissertação enquadra-se no projeto “ATHENA” (All-Terrain Hexapod for Environment Navigation Adaptability) e tem o intuito de desenvolver um modelo de um robô hexápode, tal como o seu controlo para locomoção em diferentes tipos de marcha. Ademais, procura-se também nesta dissertação a previsão da eficiência da marcha em diferentes topologias de terreno, recorrendo a técnicas de aprendizagem supervisionada para prever qual a marcha mais adequada em cada um. Após uma introdução ao tema, é realizada uma revisão dos principais conceitos para o desenvolvimento do projeto. Posteriormente, é abordado o desenvolvimento do protótipo do robô hexápode, englobando a seleção de todo o hardware utilizado e o desenvolvimento dos diferentes componentes do modelo físico final. Concluída a parte relativa ao protótipo, é feita uma abordagem à cinemática e controlo do robô, onde se aborda a cinemática direta e cinemática inversa da perna, assim como curvas de Bézier para definição da trajetória do pé. Ainda nesta secção, é apresentada a aplicação dos conceitos no robô de forma a permitir a locomoção do mesmo em diferentes tipos de marcha, utilizando para o efeito Arduíno e a linguagem de programação Python. De seguida, é feita a avaliação das diferentes marchas em diferentes tipos de terreno, recorrendo à utilização de um IMU e de visão por computador para recolha de dados propriocetivos e dados exterocetivos, utilizados posteriormente num algoritmo de aprendizagem supervisionada para perceber qual a marcha mais adequada para cada topologia. Por fim, é feita uma avaliação final de todo o trabalho desenvolvido.The growing interest in the field of mobile robotics has led to an increase in research and development of autonomous mobile robots, particularly for performing tasks that are dangerous for humans. For movement in complex environments, hexapod robots are a good choice due to their ability to adapt to different types of terrain thanks to their high number of stable gait. In addition, the body stability of hexapod robots is considered a priority for navigation in challenging environments The dissertation is part of the "ATHENA" (All-Terrain Hexapod for Environment Navigation Adaptability) project and aims to develop a model of a hexapod robot, as well as its control for movement in different types of gait. In addition, this dissertation also aims to predict the efficiency of gait in different types of terrain, using supervised learning techniques to predict the most appropriate gait in each one. After an introduction to the topic, a review of the main concepts for the development of the project is carried out. Subsequently, the development of the hexapod robot prototype is addressed, including the selection of all the hardware used and the development of the different components of the final physical model. Once the prototype section is completed, an approach to the kinematics and control of the robot is made, where the direct kinematics and inverse kinematics of the leg are addressed, as well as Bézier curves for defining the foot trajectory. In this section, the application of the concepts on the robot is also presented in order to allow its movement in different types of gait, using Arduino and the Python programming language. Next, the evaluation of the different gaits on different types of terrain is made, using an IMU and computer vision for proprioceptive and exteroceptive data collection, which are subsequently used in a supervised learning algorithm to understand the most appropriate gait for each typology. Finally, a final evaluation of all the work developed is made

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)