Artigos
URI permanente para esta coleçãohttps://repositorio.fei.edu.br/handle/FEI/792
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Resultados da Pesquisa
- RoboFEI@Home: Winning Team of the RoboCup@Home Open Platform League 2022(2023-03-24) MAROSTICA, N.G.; AGUIAR, N. A. G. M.; PIMENTAL, F. A. M.; Aquino-Junior P.T.© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.For the first time, the HERA robot won the RoboCup@Home in the Open Platform League in Bangkok, Thailand. This robot was designed and developed by the RoboFEI@Home team, considering all mechanical, electronic, and computational aspects. It is an Open League platform capable of performing autonomous tasks in home environments, in addition to human-robot interaction, collaborating with people who share the same environment. In this edition of the competition, the platform presented advances in the methods of interacting with people and social navigation. Interaction with people and objects is supported by image segmentation processes, enhancing environment perceptions and people recognition during tasks.
- The Inclusive Potential of Educational Robotics(2022-10-18) CANET, A. M. D.; Flavio Tonidandel© 2022 IEEE.Educational Robotics favors the development of reasoning, teamwork and the socialization of knowledge. In this work, using this educational technology as a learning mediator, its inclusive potential for students with disabilities in elementary school questioned. The objective of this study is verify the inclusive potential of educational robotics and what are the difficulties the robotics teachers present in the inclusion of students with disabilities. This research is qualitative and quantitative. It involves a bibliographic research and a questionnaire answered by the Professor of Support to Pedagogical Projects of Educational Technologies (PAPP TEC) of the Municipal Schools of São Bernardo do Campo. The questionnaire used the free Google Forms tool. The multiple-choice answers received statistical treatment and the open question analyzed using Bardin's content analysis. In the questionnaire and in the semi-structured interview, the teachers pointed out the need for training actions, collaborative action by support professionals (Technical Guidance Team and specialist teachers in the areas of disabilities) and access to assistive technology for the development of the inclusive potential of robotics.
- Case Study of student with neuromotor disability in the Educational Robotics project in Elementary School I(2022) Canet A.M.D.; Tonidandel F.© 2022 IEEE.In this investigation, using educational robotics as a mediator of learning, its inclusive potential for students with severe neuromotor impairment in elementary school was questioned. The objective of this work is to list the strategies and assistive technologies needed for children diagnosed with chronic non-evolving encephalopathy, with a motor condition of tetraparesis, who are attending Elementary School I, to be able to perform the activities proposed in the Educational Robotics classes. The hypothesis raised is that with the necessary adaptations the student can improve their functional performance and carry out school activities with greater autonomy and independence. This research is qualitative. It involves two phases: bibliographic research and a case study involving two elementary school students diagnosed with non-progressive chronic encephalopathy, with a motor condition of tetraparesis. The following used for the analysis of functional performance: the filming of the child before and after the use of the adaptations, the PEDI (Pediatric Evaluation of Disability Inventory), the ICF (International Classification of Functioning) and the PAPP TEC semi-structured interview. It concluded that virtual robotics through a software with screen scanning and interconnected boards of communication proved a possibility for adapting children who do not have conventional access to the assembly and programming parts of the robot, especially those with severe neuromotor disability who obtain the adaptive switch. With the use of adaptations, the student showed an improvement in her occupational performance and made it possible for her to participate in activities as a protagonist and not just as an observer.
- Computer Vision Based on a Modular Neural Network for Automatic Assessment of Physical Therapy Rehabilitation Activities(2022-01-05) FRANCISCO, J. A.; Paulo RodriguesAuthorPhysical rehabilitation techniques during the treatment of clinical pathology are one of the most challenging areas for the medical structure, patients, and families. In large and continental countries, remote monitoring of this treatment is essential. However, equipment and medical follow-up during exercises still have high costs. With the improvement of computer vision and machine learning techniques, some computational, less expensive alternatives have been proposed in the literature. However, monitoring patients during physical rehabilitation exercises with the help of artificial intelligence by a health professional, especially from the capture of visual signals, is still a challenge and poorly explored in the scientific-technological literature. This work aims to propose a new methodology based on computer vision and machine learning for remote tracking of the body joints of patients during physiotherapy rehabilitation exercises. As a new contribution, this work presents a modular neural network architecture composed of two modules: one for detecting physical exercises and another for measuring how much is correct. Another contribution is a strategy for expanding databases, considering that generic databases for this type of exercise are rare on the internet. The results showed that both modules obtained more than 90% of accuracy in recognition and their respective validation.
- Discrete-event simulation of an irrigation system using Internet of Things(2022-06-01) GOMES ALVES, R.; Rodrigo Maia; Fabio Lima© 2003-2012 IEEE.Agricultural water consumption represents 69% of all freshwater used on the planet. In addition, it is necessary to increase food production by 50% by 2050. The use of Internet of Things platforms to carry out the sensing and monitoring of the agricultural environment is increasingly present in the literature. One of the difficulties that such platforms face is to validate the platform's operation in different irrigation systems, as it is often necessary for specialists to work in the connection of sensors and actuators that already exist on farms or that are defined in the design of such systems. Within this context, a discrete-event simulation of an irrigation system integrated into an Internet of Things platform was developed in this work. The digital manufacturing software Plant Simulation was used to perform the discrete event simulation. An OPC UA server establishes real-time communication between the Internet of Things platform and the simulation software. Thus, farmers may verify, in real-time, how a given irrigation prescription, sent by the IoT platform, takes place in the irrigation system.
- Dynamic Power Management on a Mobile Robot(2021-12-03) De Carvalho Techi R.; Plinio Thomaz Aquino Junior© 2021 IEEE.Mobile robots must operate autonomously for sev-eral hours without interruption in battery charging. Energy optimization systems and methods are essential for the applicability of this technology. Dynamic Power Management (DPM) has the objective to reduce a system's total energy demand, through idleness exploitation. If the equipment is not in use, its energy dissipation should be as low as possible. This work presents the existing DPM methods analysis, systems requirements to make it eligible for the DPM, and also the management applicability analysis on a mobile robot.
- A bipartite graph approach to retrieve similar 3D models with different resolution and types of cardiomyopathies(2022-05-01) Leila Bergamasco; LIMA, K.R.P.S.; ROCHITTE, C. E.; NUNES, F. L. S.Three-dimensional (3D) model retrieval uses content-based image retrieval (CBIR) techniques to search for the most similar 3D objects in a dataset, usually considering their geometry and organization in a feature vector. Feature vectors from different objects were compared to establish their similarities. Although this type of comparison typically uses metric distances, such metrics present limitations when the vector lengths are different. Signal-based descriptors are a promising approach for extracting features from 3D objects, but they generate feature vectors with different lengths. Thus, new methods for measuring the similarity are required. This study proposes an approach to 3D model retrieval as a network flow problem using bipartite graphs. The approach was applied to support the diagnosis of cardiomyopathies, considering 3D objects reconstructed from cardiac images of the left ventricle. We achieved an AUC value of 0.93 under the best retrieval scenario. The results also indicate that modeling a 3D model retrieval technique as a network flow problem using graphs can provide a promising manner to compare 3D objects with different shapes and sizes. This strategy, coupled with personal patient data, achieves better results than methods using classical comparison approaches.
- Assessing distributed collaborative recommendations in different opportunistic network scenarios(2020-08-01) BARBOSA, L. N.; GEMMELL, J. F.; HORVATH, M.; HEIMFARTH, T.© 2020 Inderscience Enterprises Ltd.Mobile devices are common throughout the world, even in countries with limited internet access and even when natural disasters disrupt access to a centralised infrastructure. This access allows for the exchange of information at an incredible pace and across vast distances. However, this wealth of information can frustrate users as they become inundated with irrelevant or unwanted data. Recommender systems help to alleviate this burden. In this work, we propose a recommender system where users share information via an opportunistic network. Each device is responsible for gathering information from nearby users and computing its own recommendations. An exhaustive empirical evaluation was conducted on two different data sets. Scenarios with different node densities, velocities and data exchange parameters were simulated. Our results show that in a relatively short time when a sufficient number of users are present, an opportunistic distributed recommender system achieves results comparable to that of a centralised architecture.
- Evaluation of ROS Navigation Stack for Social Navigation in Simulated Environments(2021-08-05) PIMENTEL, F. A. M.; Plinio Thomaz Aquino Junior© 2021, The Author(s), under exclusive licence to Springer Nature B.V.Accuracy and safety are necessary characteristics in social navigation. These characteristics still constitute a challenge in this area. Yet, human comfort is the main goal in interactions involving human beings. The ROS Navigation Stack (RNS) allows the variation of local path planning methods. This paper consists in a comparative study of methods related to social navigation. This study promotes better social navigation on Home Environment Robot Assistant (HERA). This is a robot platform developed by FEI University Center. This work evaluated various parameter combinations: type of environments, types of obstacles, local and global planning algorithms and costmaps. The work also evaluated people in static, dynamic and interacting ways. This study observed aspects of safety, accuracy of estimated time and space. Other aspects observed are the smooth trajectory realized and respect for personal space. The experiments performed 1000 attempts for 37 combinations of methods, environments and sensors. In total, the experiments counted 37000 attempts. With these experiments, was possible to select a configuration for the navigation system. The point to the Timed Elastic Band (TEB) as a local planner and a proxemic costmap as a good combination. The results reach 97.6% of success in a more complex environment with this combination.
- Recent Nature-Inspired Algorithms for Medical Image Segmentation Based on Tsallis Statistics(2020-03-09) LOPES, GUILHERME ALBERTO WACHS; SANTOS, R. M.; SAITO, N.T.; RODRIGUES, P. S.Recently, many algorithms have emerged inspired by the biological behavior of animal life to deal with complicated applications such as combinatorial optimization. One of the most critical discussions involving these algorithms is concerning their objective functions. Also, recently, many works have demonstrated the efficiency of Tsallis non-extensive statistics in several applications. However, this formalism has not yet been tested in most recent bio-inspired algorithms as an evaluation function. Thus, this paper presents a study of seven of the most promising bio-inspired algorithms recently proposed (a maximum one decade), from this entropy applied to the multi-thresholding segmentation of medical im- ages. The results show the range of values of q , the so-called non-extensivity parameter of the Tsallis entropy, for which the algorithms tested here have their best performance. It is also demonstrated that the Firefly algorithm (FFA) is the one that obtained the best per- formance in terms of segmentation, and Grey Wolf Optimizer (GWO) presents the fastest convergence.