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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Mendonca, Vanessa Santos, Mikael Munoz, Daniel M. Humberto Llanos, Carlos Federal Institute of Brasilia Department of Computer Science Brazil Mechatronics Graduate Program Department of Mechanical Engineering Brazil Federal Institute of Brasilia Department of Agronomy Brazil University of Brasilia Faculty of Gama Electronics Engineering Undergraduate Program Brasilia Brazil

ISBN: (纸本)9798350374575

Technological advancements are increasingly evident across various sectors, including automobiles, industry, and healthcare. In precision agriculture, significant progress has been made, with AgroTICs and Smart Agriculture gaining substantial traction in the market. However, a gap remains between cutting-edge technology and family farming, presenting a challenge from both social and applied research perspectives. However, there is still a gap between cutting-edge technology and family farming, which creates a challenge from a social and applied research point of view. In this context, this paper proposes a monitoring model based on Fuzzy Logic and sensor automation applied to estimate the health of a corn crop. The proposed Fuzzy inference system involves calculating an indicator of nutrients as well as the average color and area of corn plants. The nutrient indicator is automatically computed by an ESP32 microcontroller using sensor readings, while the average color and area inputs are manually entered via a mobile application. Additionally, the Fuzzy inference is integrated into the ESP32. The model underwent experimental validation on the health of the plantation, and the results were evaluated in four areas: one was designated for testing, and three were for validation. The model achieved an accuracy of 97.5% in Scenario 3, categorized as 'Very Favorable', and an accuracy of 65% in Scenarios 2 and 4, categorized as 'Unfavorable'. The implications of this research contribute to the advancement of AgroTICs among small producers, with the potential to enhance and automate the monitoring of their harvest production. © 2024 IEEE.

关键词： Agribusiness

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Project Edubot: Exploring Pedagogical Approaches in High School Robotics Education

Project Edubot: Exploring Pedagogical Approaches in High Sch...

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2024 Brazilian Symposium on Robotics (SBR), and 2024 Workshop on Robotics in Education (WRE)

作者： Isabela Nunes Daltro João Victor Silva Santos Guilherme Barbosa De Sousa Rodrigo Martins M. A. Pastrana Roberto De Souza Baptista Mechatronics Engineering Undergraduate Program Department of Mechanical Engineering Mechatronics Graduate Program Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798350391084

ISBN: (纸本)9798350391091

This study focus on passive and active learning within the context of robotics education on public high schools. By synthesizing research findings and practical insights, this paper offers valuable recommendations for educators aiming to optimize the delivery of robotics education in public high schools, addressing the significance of the utilization of appropriate resources and technologies to support effective instruction. We implemented two distinct teaching methodologies to compare and study students' reactions and learning outcomes: Group A experienced a passive methodology, while Group B engaged with an active methodology. We conducted a survey and the results show that the majority of the students prefer the active approach used in classes.

关键词： Surveys Conferences Education Active learning Collaboration Problem-solving Robots Creativity

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Heading Angle Estimation Using Intelligent Fusion for Autonomous Vehicles

Heading Angle Estimation Using Intelligent Fusion for Autono...

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2023 Advances in Science and engineering Technology International Conferences, ASET 2023

作者： Barakat, Ali A. Jardat, Mohammad A. Elsergany, Ahmed M. Sherif, Nidal A. American University of Sharjah Mechanical Engineering Department Sharjah United Arab Emirates American University of Sharjah Mechatronics Engineering Graduate Program Sharjah United Arab Emirates

ISBN: (纸本)9781665454742

Low-cost navigation systems for ground vehicles often rely on the fusion with Global Positioning System (GPS) for improved state estimation. In this study a low-cost gyroscope is fused with a GPS for improved vehicle heading angle estimation using several Artificial Intelligence (AI) based architectures that include Shallow Neural Networks (SNN), Multi-Layer Neural Networks (MLNN), and Adaptive Neuro- Fuzzy Inference Systems (ANFIS). The primary goal behind using AI based sensor fusion is to obtain a highly accurate vehicle heading estimation suitable for autonomous navigation applications. When available, the GPS signal is used to correct the vehicle's heading angle. The neural networks and ANFIS methods both use the difference between the GPS signal and the heading angle from the integrated gyroscope as inputs. The performance achieved is shown and analyzed. According to the results obtained, the MLNN provides the most accurate heading estimates. © 2023 IEEE.

关键词： Global positioning system

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Intelligent Adaptive RRT∗Path Planning Algorithm for Mobile Robots

Intelligent Adaptive RRT∗Path Planning Algorithm for Mobile...

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2023 Advances in Science and engineering Technology International Conferences, ASET 2023

作者： Khattab, Omar Yasser, Ahmed Jaradat, Mohammad A. Romdhane, Lotfi American University of Sharjah Mechatronics Engineering Graduate Program Sharjah United Arab Emirates American University of Sharjah Mechanical Engineering Department Sharjah United Arab Emirates

ISBN: (纸本)9781665454742

In this paper a new variant of the widely used Rapidly exploring Random Tree (RRT∗) algorithm is proposed. The main goal of this variant is to improve the efficiency of the generated path, in both computation time and the quality of the path. In a previous work by the authors, an improved version RRT∗N was proposed, where a normal probability distribution was used to control the generation of the random nodes. The proposed variant utilizes an intelligent fuzzy logic system (FLS) to control the generation of the random nodes and commands the robot to the required target introducing an intelligent fuzzy adaptive RRT∗N path planning approach (FA-RRT∗N). The proposed approach not only reduced the time required about 29.5 % of the time required by the RRT∗, but also generally resulted in shorter path about 63% of the path generated by the traditional RRT∗. © 2023 IEEE.

关键词： Motion planning

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Nitrogen Pretreatment of Growth Substrates for Vacancy-Saturated MoS2

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ACS Applied Materials and Interfaces 2023年第36期15卷 42746-42752页

作者： Yao, Yu-Chi Wu, Bo-Yi Chin, Hao-Ting Yen, Zhi-Long Ting, Chu-Chi Hofmann, Mario Hsieh, Ya-Ping Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Department of Physics National Taiwan University Taipei10617 Taiwan Graduate Institute of Opto-Mechatronics Department of Mechanical Engineering National Chung Cheng University Chia-Yi62102 Taiwan International Graduate Program of Molecular Science and Technology National Taiwan University Taipei10617 Taiwan Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei10617 Taiwan

Two-dimensional transition-metal dichalcogenides (2D TMDCs) are considered promising materials for optoelectronics due to their unique optical and electric properties. However, their potential has been limited by the occurrence of atomic vacancies during synthesis. While post-treatment processes have demonstrated the passivation of such vacancies, they increase process complexity and affect the TMDC’s quality. We here introduce the concept of pretreatment as a facile and powerful route to solve the problem of vacancies in MoS2. Low-temperature nitridation of the sapphire substrate prior to growth provides a nondestructive method to MoS2 modification without introducing new processing steps or increasing the thermal budget. Spectroscopic characterization and atomic-resolution microscopy reveal the incorporation of nitrogen from the sapphire surface layer into chalcogen vacancies. The resulting MoS2 with nitrogen-saturated defects shows a decrease in midgap states and more intrinsic doping as confirmed by ab initio calculations and optoelectronic measurements. The demonstrated pretreatment method opens up new routes toward future, high-performance 2D electronics, as evidenced by a 3-fold reduction in contact resistance and a 10-fold improved performance of 2D photodetectors. © 2023 American Chemical Society

关键词： Molybdenum compounds

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Behavior-Based Control with Learning from Demonstration for Path Following Applied to Mobile Robots Soccer

Behavior-Based Control with Learning from Demonstration for ...

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IEEE Latin American Robotics Symposium, LARS

作者： Matheus de S. Luiz M. A. Pastrana Guilherme Achilles de Oliveira e Aguiar R. B. Costa Luiz F. Rodrigues e Silva Faculty of Gama Electronics Engineering Undergraduate Program Department of Mechanical Engineering Mechatronics Graduate Program Faculty of Technology Mechatronics Engineering Undergraduate Program Faculty of Gama Aerospace Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

Learning from Demonstration (LfD) enables robots to learn new tasks through an imitation process. This methodology can be combined with Behavior-Based Control (BBC), which facilitates the abstraction of behaviors for the robot by dividing them into micro-behaviors. These can be implemented using Artificial Neural Networks trained by bio-inspired algorithms. In this work, a novel methodology based on the LfD and BBC methods is proposed for controlling soccer robots, specifically for the Very Small Size Soccer (VSSS) category, which demands quick and dynamic responses. Simulations using CoppeliaSim were conducted to demonstrate how the proposed methodology can be used for path planning and path-following problems in the IEEE VSSS category.

关键词： Measurement Training Heuristic algorithms Artificial neural networks Turning Robustness Path planning Robots Optimization Sports

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Application of Recurrence Plots and VGG Deep Learning Model to the Study of Condition Monitoring of Robotic Grinding

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International Journal of Precision engineering and Manufacturing 2023年第9期24卷 1675-1683页

作者： Chung, Kuan-Jung Dai, Cheng-Han Chiang, Tung-Chun Xie, June-Jia Lin, Ming-Tzer Department of Mechatronics Engineering National Changhua University of Education Changhua500 Taiwan Graduate Institute of Precision Engineering National Chung Hsing University Taichung402 Taiwan Doctoral Program in Industrial and Smart Technology Academy of Circular Economy National Chung Hsing University Nantou540 Taiwan

This study adopted AI to identify the normal and abnormal vibration signals generated during robotic grinding. This study classified four fundamental factors affecting grinding into three levels to obtain a widely used result and designed an L9(3 4) orthogonal array for the grinding experiment. During experimentation, part of the grinding wheels was added weight to produce abnormal vibration signals, which an accelerometer would measure. The study transformed the collected vibration signals into recurrence plots and conducted model training with VGG16 CNN architecture. Finally, this study tested a model with 89.6% training accuracy. The results showed the model could identify whether the recurrence plots stand for normal or abnormal vibrations, with an accuracy of 85%. This means it could predict normal and abnormal grinding conditions and help avoid problems caused by abnormal vibrations. © 2023, The Author(s), under exclusive licence to Korean Society for Precision engineering.

关键词： Grinding (machining)

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Implementation of a PID Controller using Online Tuning Applied to a Mobile Robot Obstacle Following/Avoidance

Implementation of a PID Controller using Online Tuning Appli...

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Argentine Conference on Electronics (CAE)

作者： M. A. Pastrana L. H. Oliveira D. A. Mendes Douglas. L. Silva Jose Mendoza-Peñaloza Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

The implementation of a bioinspired PID-based controller with online tuning capabilities is developed for obstacle following/avoidance of a nonholonomic mobile robot. An innovative mixture of the conventional PID controller and particle swarm optimization (PSO), which has a strong capability of adaptation across unknown scenarios, reduced objective error, brings us a novel online tuning methodology that can derive optimal controller parameters for a given scenario. It is appropriate for a kind of plant without prior knowledge or established mobile robot model. Computer simulation for obstacle following/avoidance is carried out in four different scenarios using the CoppeliaSim software and the EVA mobile robot platform. The effectiveness of the proposed control algorithm is demonstrated trough the simulation experiment, which shows its superior performance in the training scenario, including an overshoot of 20.1 %, a settling time of 10 seconds, and a steady-state error of 0.76%.

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Design and Performance Comparison of Current References for a 32-bit Microcontroller Using 22nm Technology

Design and Performance Comparison of Current References for ...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Eduardo A. Barcelos Pâmela R. A. N. Campagnucci Daniel M. Muñoz Wellington A. Amaral Sandro A. P. Haddad Department of Mechanical Engineering Faculty of Technology Mechatronics Graduate Program Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

With the advancement of semiconductor technologies, the need for efficient power management solutions in integrated systems, such as RISC-V architecture-based microcontrollers, becomes increasingly critical. However, there is a lack of studies comparing current reference architectures in terms of performance and robustness, particularly in 22nm technologies. In this paper, we present a comparative analysis of two current reference designs implemented in the same technology-referred to as Reference Design A and Reference Design B. We focus on their approaches to thermal compensation, supply stability, and layout optimizations. Through simulations and experimental tests, we evaluate the performance of each design within a power management system that includes DC-DC converters and LDO regulators. Our results indicate that Design A exhibits superior power supply rejection with a PSRR of -85 dB, while Design B demonstrates enhanced energy efficiency and thermal stability, achieving a nominal current of 5.14 μA and a temperature coefficient of 16.21 ppm. These findings underscore the importance of balancing energy efficiency, thermal stability, and power supply variation rejection when selecting current references for low-power, high-reliability applications, such as those in the Internet of Things (IoT).

关键词： Resistance Microcontrollers Power system management Stability criteria Energy efficiency Robustness Circuit stability Thermal analysis Internet of Things Thermal stability

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A 22nm CMOS PFM Buck Converter Used in a 32-Bit RISC-V Microcontroller for IoT Applications

A 22nm CMOS PFM Buck Converter Used in a 32-Bit RISC-V Micro...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Luiz H. N. Oliveira Wellington A. Amaral Sandro A. P. Haddad Daniel M. Muñoz Eduardo A. Barcelos Vinícius V. M. Sotero Emmanuel K. M. Jonhson Pâmela R. A. N. Campagnucci Luis V. N. Lima Department of Mechanical Engineering Faculty of Technology Mechatronics Graduate Program University of Brasilia Brasilia DF Brazil Faculty of Gama Electronics Engineering Undergraduate Program

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

The demand for efficient power management solutions in electronic devices has increased significantly, especially for microcontrollers operating in low-power modes. This article presents the design and implementation of a Pulse Frequency Modulation (PFM)-based buck converter for applications in 32-bit microcontrollers using 22nm CMOS technology. The methodology involves the development of a Constant On Time (COT) architecture that maintains a fixed duration for the activation of the high-side MOSFET, using a monostable multivibrator to generate the necessary timing signals. The converter's performance was simulated under various load conditions and process corners to evaluate its efficiency and output characteristics. The results show that the proposed buck converter achieves high efficiency, with peak values above 95%, while maintaining a low output ripple. Specifically, the converter exhibits an efficiency of 93.4% at a load of 1mA, with output ripple voltages as low as 2.20 mV under ideal conditions. The contributions of this work lie in the advancement of PFM converter technology for modern microcontroller applications, demonstrating the potential of 22nm CMOS processes to improve power efficiency and performance.

关键词： Semiconductor device modeling Performance evaluation MOSFET Buck converters Microcontrollers Power system management Multivibrators Timing Internet of Things Load modeling

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