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2.
Bioinspir Biomim ; 18(6)2023 09 27.
Artigo em Inglês | MEDLINE | ID: mdl-37714177

RESUMO

This study aims to present a novel flocking algorithm for robotic fish that will aid the study of fish in their natural environment. The algorithm, fish-inspired robotic algorithm (FIRA), amalgamates the standard flocking behaviors of attraction, alignment, and repulsion, together with predator avoidance, foraging, general obstacle avoidance, and wandering. The novelty of the FIRA algorithm is the combination of predictive elements to counteract processing delays from sensors and the addition of memory. Furthermore, FIRA is specifically designed to work with an indirect communication method that leads to superior performance in collision avoidance, exploration, foraging, and the emergence of realistic behaviors. By leveraging a high-latency, non-guaranteed communication methodology inspired by stigmergy methods inherent in nature, FIRA successfully addresses some of the obstacles associated with underwater communication. This breakthrough enables the realization of inexpensive, multi-agent swarms while concurrently harnessing the advantages of tetherless communication. FIRA provides a computational light control algorithm for further research with low-cost, low-computing agents. Eventually, FIRA will be used to assimilate robots into a school of biological fish, to study or influence the school. This study endeavors to demonstrate the effectiveness of FIRA by simulating it using a digital twin of a bio-inspired robotic fish. The simulation incorporates the robot's motion and sensors in a realistic, real-time environment with the algorithm used to direct the movements of individual agents. The performance of FIRA was tested against other collective flocking algorithms to determine its effectiveness. From the experiments, it was determined that FIRA outperformed the other algorithms in both collision avoidance and exploration. These experiments establish FIRA as a viable flocking algorithm to mimic fish behavior in robotics.


Assuntos
Robótica , Animais , Comunicação , Instituições Acadêmicas , Algoritmos , Simulação por Computador , Peixes
4.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 4616-4619, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33019022

RESUMO

Human Activity Recognition (HAR) is a central unit to understand and predict human behavior. HAR has been used to estimate the levels of a sedentary, monitor lifestyle habits, track the levels of people's health, or build a recommendation system. Many researchers have utilized the inertial measurement unit as an input tool to explore the HAR land. The recurrence plot (RP) technique recently has its applications diverse in various areas. From the recurrence plot, a machine-auto or hand-crafted approach can be used to extract feature vectors. While the machine-auto based approach has been reported in the literature, the latter hand-crafted based method has not. For that reason, this paper evaluated and demonstrated the feasibility of utilizing Recurrence Quantification Analysis (RQA), which was a typical hand-crafted method from RP, to classify human activities. A Linear Discriminant Analysis classifier yielded a 95.08% accuracy, which belonged in the top accuracy reported in the literature. Compare to the machine-auto or end-to-end approach, RQA is a far less complicated and more lean system that should be further analyzed in a HAR application.


Assuntos
Mãos , Atividades Humanas , Análise Discriminante , Humanos
5.
Phys Med ; 30(7): 809-15, 2014 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-25172392

RESUMO

This report, compiled by experts on the treatment of mobile targets with advanced radiotherapy, summarizes the main conclusions and innovations achieved during the 4D treatment planning workshop 2013. This annual workshop focuses on research aiming to advance 4D radiotherapy treatments, including all critical aspects of time resolved delivery, such as in-room imaging, motion detection, motion managing, beam application, and quality assurance techniques. The report aims to revise achievements in the field and to discuss remaining challenges and potential solutions. As main achievements advances in the development of a standardized 4D phantom and in the area of 4D-treatment plan optimization were identified. Furthermore, it was noticed that MR imaging gains importance and high interest for sequential 4DCT/MR data sets was expressed, which represents a general trend of the field towards data covering a longer time period of motion. A new point of attention was work related to dose reconstructions, which may play a major role in verification of 4D treatment deliveries. The experimental validation of results achieved by 4D treatment planning and the systematic evaluation of different deformable image registration methods especially for inter-modality fusions were identified as major remaining challenges. A challenge that was also suggested as focus for future 4D workshops was the adaptation of image guidance approaches from conventional radiotherapy into particle therapy. Besides summarizing the last workshop, the authors also want to point out new evolving demands and give an outlook on the focus of the next workshop.


Assuntos
Educação , Tomografia Computadorizada Quadridimensional , Planejamento da Radioterapia Assistida por Computador , Radioterapia Guiada por Imagem , Imageamento por Ressonância Magnética , Movimento
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