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2023 International Conference on Unmanned Aircraft Systems, ICUAS 2023

作者： Braathen De Carvalho, Kevin De Oliveira, Iure Rosa L. Brandao, Alexandre S. Universidade Federal de Viçosa Nucleus of Specialization in Robotics Department of Electrical Engineering Graduate Program in Computer Science MG Viçosa36570-900 Brazil Federal University of Viçosa Department of Electrical Engineering MG Viçosa Brazil

ISBN: (纸本)9798350310375

Unmanned Aerial Vehicles (UAVs) are widely used in various applications, from inspection and surveillance to transportation and delivery. Navigating UAVs in complex 3D environments is a challenging task that requires robust and efficient decision-making algorithms. This paper presents a novel approach to UAV navigation in 3D environments using a Curriculum-based Deep Reinforcement Learning (DRL) approach. The proposed method utilizes a deep neural network to model the UAV's decision-making process and to learn a mapping from the state space to the action space. The learning process is guided by a reinforcement signal that reflects the performance of the UAV in terms of reaching its target while avoiding obstacles and with energy efficiency. Simulation results show that the proposed method has a positive trade off when compared to the baseline algorithm. The proposed method was able to perform well in environments with a state space size of 22 millions, allowing the usage in big environments or in maps with high resolution. The results demonstrate the potential of DRL for enabling UAVs to operate effectively in complex environments. © 2023 IEEE.

关键词： Reinforcement learning

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Suppression of Vibration in PMSM Caused by Time-Varying Load for Reciprocating Compressor

Suppression of Vibration in PMSM Caused by Time-Varying Load...

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International Conference on Electrical Machines, ICEM

作者： Soo-Hwan Park Jae-Hyun Kim Chi-Sung Park Yun-Jae Won Myung-Seop Lim Department of Mechanical Robotics and Energy Engineering Dongguk University Seoul South Korea School of Mechanical Engineering Yeungnam University Daegu South Korea Department of Automotive Engineering Hanyang University Seoul South Korea Department of Automotive Engineering (Automotive-Computer Convergence) Hanyang University Seoul South Korea

ISBN: (数字)9798350370607

ISBN: (纸本)9798350370614

This paper deals with the vibration characteristics of permanent magnet synchronous motors (PMSMs) when there is time-varying load generated in the reciprocating compressor. As the reciprocating mechanism is necessary for compressing the refrigerant, the time-varying load torque is inevitable in compressor. However, this load torque affects to the system dynamics such as the speed fluctuation. These speed ripple cause unexpected vibration characteristics because they induce sideband components in the time harmonics of the electromagnetic force of PMSM. Therefore, we analyzed the vibration characteristics of PMSM according to time harmonics variation and conduct a study to suppress sideband vibration by adopting harmonic current injection method.

关键词： Vibrations Magnetic flux Torque System dynamics Velocity control Vibration measurement Amplitude modulation Harmonic analysis Time-varying systems Predictive control

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MOSFET Based Active Rectifier Design in Wireless Capacitive Power Transfer for Electric Vehicles

MOSFET Based Active Rectifier Design in Wireless Capacitive ...

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Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Klemens Raphael Dragon Zener Sukra Lie Aam Muharam Juan Luciano Ika Muhamad Arjuna Perdana Amin Abdul Hapid Computer Engineering Department Automotive and Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Research Center for Transportation Technology Badan Riset dan Inovasi Nasional Bandung Jawa Barat Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

While the rise of electric vehicles reflects a push for clean energy as envisioned by international agreements like the Paris Agreement, wireless charging's convenience can overcome limitations and hasten their adoption, making it a strategic step alongside regulations such Permenhub No. 15/2022 and SDG 9 “Industry, Innovation, and Infrastructure” for cleaner air and sustainable transportation. The aim is to convert the high frequency AC voltage from the coupling capacitor into a stable DC voltage. Further increase the system sensitivity to the load variations, by designing a MOSFET based active rectifier. By changing load parameters, the accuracy of PFC adaptation to the battery State of Charge (SOC) obtained is at 98% with 2% tolerance for errors. It is concluded that the research is said to be successful because it has met the parameters of general research hypothesis where the system is able to convert high frequency AC voltage into a stable DC voltage.

关键词： Wireless communication MOSFET Wireless sensor networks Rectifiers High-voltage techniques Electric vehicles Batteries State of charge High frequency Voltage control

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Applying CNN Models with Stereo Camera for Object Detection and Distance Estimation in Automatic Micro Electric Vehicle (MEVi)

Applying CNN Models with Stereo Camera for Object Detection ...

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Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Farrell Putra Harimanto Nurul Hasanah Muhammad Khristamto Aditya Pradana Muhammad Nurul Puji Computer Engineering Department Automotive & Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Research Center for Smart Mechatronics National Research and Innovation Agency KST Samaun Samadikun Bandung Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

Technological advancements in the automotive industry are currently focused on autonomous driving systems or driver assistance systems. Depth estimation is also an important feature of the autonomous driving system as it can accurately estimate the distance to the detected objects. In current developments technologies such as stereo cameras are more popular for a more accurate depth estimation. The process for object detection consists of a combination of classification, localization, and segmentation. Deep convolutional neural networks are the basis of object detection. The methods for object detection are divided into two categories namely the Region Proposal-based method such as RCNN, and the Classification-based method which provides for methods such as YOLO and MobileNet. As a part of the research conducted by the National Research and Innovation Agency (BRIN) on Automatic Micro Electric Vehicles or MEVi, this paper analyzed and compared the performance of several CNN models for object detection as well as the performance of depth sensing using ZED stereo camera which was used for the autonomous system in MEVi. Among several models that had been compared, YOLO v8 model demonstrates high accuracy and moderate speed as indicated by its high mAP (0.50) and FPS (38.46). Based on depth sensing results, the accuracy of distance measurement also depended on brightness and environment with the average of accuracy achieved indoors was 98.2% and outdoors was 96.3%.

关键词： YOLO Accuracy Depth measurement Brightness Cameras Electric vehicles Distance measurement Sensors Convolutional neural networks Autonomous vehicles

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Design of Volumetric Magnetic Induction Tomography (VMIT) System Using COMSOL Simulation

Design of Volumetric Magnetic Induction Tomography (VMIT) Sy...

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International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET)

作者： Muhammad Nurul Puji Prawito Prajitno Warsito Purwo Taruno Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Electronic and Instrumentation Physics of The Department of Physics Universitas Indonesia Depok Indonesia C-TECH LABS Edwar Technology Tangerang Indonesia

ISBN: (数字)9798350389920

ISBN: (纸本)9798350389937

Magnetic Induction Tomography (MIT) is a low-resolution imaging technique used to reconstruct the magnetic permeability distribution of an object. COMSOL Simulation of VMIT (Volumetric Magnetic Induction Tomography) system has been developed by using 8 coils as transmitter and 8 coils as receiver. The existence of sine excitation signal in the transmitter coil cause magnetic field changing, it causing emf at the receiver coil. The magnitude of the magnetic field induction is also influenced by the permeability of the medium between the transmitter and receiver coils. COMSOL and MATLAB simulation of VMIT 8 coil systems indicate that, by using ILBP algorithms, ball-shaped object with ferromagnetic materials (iron) can be reconstructed to produce a similar image. The sensitivity matrix significantly influences image reconstruction in MIT, leading to distorted elliptical images of objects, particularly when positioned at the top center, as the matrix shows homogeneity mainly in the middle area.

关键词： Coils Microwave antennas Transmitters Magnetic resonance imaging Receivers Tomography Radar antennas Permeability Magnetic fields Image reconstruction

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Energy Minimization using Custom-Designed Magnetic-Spring Actuators

Energy Minimization using Custom-Designed Magnetic-Spring Ac...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yue Yang Fu Ali U. Kilic David J. Braun Department of Electrical and Computer Engineering SyBBURE Searle Undergraduate Research Program Vanderbilt University Advanced Robotics and Control Laboratory Advanced Robotics and Control Laboratory Vanderbilt University

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This study introduces an innovative actuator that resembles a motor with a non-uniform permanent magnetic field. We have developed a prototype of the actuator by combining a standard motor, characterized by a uniform magnetic field, with a custom rotary magnetic spring exhibiting a non-uniform magnetic field. We have also presented a systematic computational approach to customize the magnetic field to minimize the energy consumption of the actuator when used for a user-defined oscillatory task. Experiments demonstrate that this optimized actuator significantly lowers energy consumption in a typical oscillatory task, such as pick-and-place or oscillatory limb motion during locomotion, compared to conventional motors. Our findings imply that incorporating task-optimized non-uniform permanent magnetic fields into conventional motors and direct-drive actuators could enhance the energy efficiency of robotic systems.

关键词： Actuators Energy consumption Limbs Systematics Prototypes Motors Minimization Magnetic fields Springs Standards

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PointNetPGAP-SLC: A 3D LiDAR-based Place Recognition Approach with Segment-level Consistency Training for Mobile Robots in Horticulture

arXiv

引用

arXiv 2024年

作者： Barros, T. Garrote, L. Conde, P. Coombes, M.J. Liu, C. Premebida, C. Nunes, U.J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal Dept. of Aeronautical and Automotive Engineering LUCAS Lab Loughborough University United Kingdom

3D LiDAR-based place recognition remains largely underexplored in horticultural environments, which present unique challenges due to their semi-permeable nature to laser beams. This characteristic often results in highly similar LiDAR scans from adjacent rows, leading to descriptor ambiguity and, consequently, compromised retrieval performance. In this work, we address the challenges of 3D LiDAR place recognition in horticultural environments, particularly focusing on inter-row ambiguity by introducing three key contributions: (i) a novel model, PointNetPGAP, which combines the outputs of two statistically-inspired aggregators into a single descriptor;(ii) a Segment-Level Consistency (SLC) model, used exclusively during training to enhance descriptor robustness;and (iii) the HORTO-3DLM dataset, comprising LiDAR sequences from orchards and strawberry fields. Experimental evaluations conducted on the HORTO-3DLM and KITTI Odometry datasets demonstrate that PointNetPGAP outperforms state-of-the-art models, including OverlapTransformer and PointNetVLAD, particularly when the SLC model is applied. These results underscore the model’s superiority, especially in horticultural environments, by significantly improving retrieval performance in segments with higher ambiguity. The dataset and the code will be made publicly available at https://***/Cybonic/*** © 2024, CC BY.

关键词： Deep learning

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Development of Detection Kidney Function Stand Alone System and Design based on Oral Ammonia Levels

Development of Detection Kidney Function Stand Alone System ...

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International Conference of computer and Informatics engineering (IC2IE)

作者： William Natasha Angeline Hansen Yosica Mariana Elioenai Sitepu Winda Astuti Melinda Siswanto Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Biotechnology Engineering Department Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

The development of detection kidney function system at the first prototype have problem with the dependence on the internet, which make not practical in the development of the system and the initial design was not ergonomic. In this work the development of the second step is done with the improvement of accuracy compared with other methods. In this work the new design of the embedded system is also applied and in term of algorithm, the system applied for woman patient. Three different types of machine learning techniques, namely K-nearest neighbors (KNN), Decision Tree and Random Forest are applied and compared. The AI-based kidney failure severity identification system with KNN algorithm had an average accuracy of 90% and 91% for training and testing accuracy, respectively. The design of the embedded system also renews with stylist, simple and practical.

关键词： Training Accuracy Machine learning algorithms Embedded systems Nearest neighbor methods Vectors Decision trees Kidney Random forests Testing

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Robust MPC Based Lateral Control System Design for Autonomous Vehicle Considering Localization Uncertainty

Robust MPC Based Lateral Control System Design for Autonomou...

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International Conference on Intelligent Transportation

作者： Sungjun Park Chanuk Yang Sangwon Han Kunsoo Huh Department of Automotive Engineering (Automotive-Computer Convergence) Hanyang University Seoul Republic of Korea Department of Automotive Engineering Hanyang University Seoul Republic of Korea BK21 Four Education and Research Program for Automotive-Software Convergence Hanyang University Seoul South Korea

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

In this paper, a lateral controller for autonomous vehicles is proposed under conditions of localization uncertainty, utilizing Robust Model Predictive Control (RMPC). Recently, localization accuracy has been largely improved through the integration of digital maps and sensor data from cameras and LiDARs. However, significant challenges remain in environments like highways, where landmarks are sparse and featureless, compromising the effectiveness of sensor data for map matching. This often leads to inaccurate vehicle positioning and, consequently, a loss of control capability. In this study, boundaries of positioning uncertainties are estimated first, and the region of uncertainty is modeled. The controller is designed to account for this uncertainty, where the constraints are adjusted to reduce chattering and biases. Simulation results demonstrate that the proposed controller effectively maintains path-tracking performance even in the presence of localization uncertainty. Additionally, this study shows that the performance can be maintained under significant localization error, indicating that it can contribute to relaxing the localization requirements.

关键词： Location awareness Robust control Road transportation Uncertainty Accuracy Laser radar Simulation Autonomous vehicles Intelligent transportation systems Predictive control

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Convergent effects of peptides on the initiation of feeding motor programs in the mollusk Aplysia

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Journal of Neurophysiology 2025年第5期133卷 1368-1379页

作者： Evans, Colin G. Barry, Michael A. Reaver, Carrie N. Patel, Paras R. Chestek, Cynthia A. Perkins, Matthew H. Jing, Jian Cropper, Elizabeth C. Department of Neuroscience Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York NY United States Department of Biomedical Engineering Biointerfaces Institute University of Michigan Ann Arbor MI United States Department of Electrical Engineering and Computer Science Neurosciences Program Robotics Program University of Michigan Ann Arbor MI United States State Key Laboratory of Pharmaceutical Biotechnology Institute for Brain Sciences Chemistry and Biomedicine Innovation Center Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology Advanced Institute for Life Sciences School of Life Sciences Nanjing University Nanjing China

Neuropeptides configure the feeding network of Aplysia. For example, egestive activity is promoted by small cardioactive peptide (SCP), and ingestive activity is promoted by a combination of feeding circuit activating peptide (FCAP) and cerebral peptide 2 (CP-2). In addition, SCP and FCAP/CP-2 have a common network effect that does not contribute to motor program specification. They increase the excitability of an interneuron, B63. In this report, we further characterized the effects of peptides on B63. We performed voltage-clamp experiments and used a step protocol to look at steady-state currents. We found that SCP and FCAP/CP-2 both induced an inward current that was virtually absent in low-sodium saline. Previous work has established that B63 is unusual in the feeding circuit in that subthreshold depolarizations are autonomously generated that can trigger motor programs. Here, we show that this autonomous activity is more frequent in the presence of peptides. Previous studies have also shown that activity of the feeding central pattern generator (CPG) can be initiated by neurons that excite B63, e.g., by cerebral buccal interneuron 2 (CBI-2), a projection neuron that triggers biting-like motor programs. Here, we show that the latency of CBI-2-induced activity is decreased by stimulation of the esophageal nerve (EN) (which releases endogenous SCP). These results, taken together with previous results, indicate that peptides that act divergently to configure network activity additionally act convergently to promote motor program induction. We present data that suggest that this arrangement facilitates brief switches between ingestive and egestive motor activity. © 2025 The Authors.

关键词： central pattern generator invertebrate modulation motor program neuropeptide

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