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UAP-BEV: Uncertainty Aware Planning Using Bird's Eye View Generated From Surround Monocular Images

UAP-BEV: Uncertainty Aware Planning Using Bird's Eye View Ge...

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IEEE international conference on automation Science and Engineering (CASE)

作者： Vikrant Dewangan Basant Sharma Tushar Choudhary Sarthak Sharma Aakash Aanegola Arun K. Singh K. Madhava Krishna Robotics Research Center IIIT Hyderabad India University of Tartu Estonia

Autonomous driving requires accurate reasoning of the location of objects from raw sensor data. Recent end-to-end learning methods go from raw sensor data to a trajectory output via Bird's Eye View(BEV) segmentation as an interpretable intermediate representation. Motion planning over cost maps generated via Birds Eye View (BEV) segmentation has emerged as a prominent approach in autonomous driving. However, the current approaches have two critical gaps. First, the optimization process is simplistic and involves just evaluating a fixed set of trajectories over the cost map. the trajectory samples are not adapted based on their associated cost values. Second, the existing cost maps do not account for the uncertainty in the cost maps that can arise due to noise in RGB images, BEV annotations. As a result, these approaches can struggle in challenging scenarios where there is abrupt cut-in, stopping, overtaking, merging, etc from the neighboring vehicles. In this paper, we propose UAP-BEV, a novel approach that models the noise in Spatio-Temporal BEV predictions to create an uncertainty-aware occupancy grid map. Using queries of the distance to the closest occupied cell, we obtain a sample estimate of the collision probability of the ego-vehicle. Subsequently, our approach uses gradient-free sampling-based optimization to compute low-cost trajectories over the cost map. Importantly, the sampling distribution is adapted based on the optimal cost values of the sampled trajectories. By explicitly modeling probabilistic collision avoidance in the BEV space, our approach is able to outperform the cost-map-based baselines in collision avoidance, route completion, time to completion, and smoothness. To further validate our method, we also show results on the real-world dataset NuScenes, where we report improvements in collision avoidance and smoothness.

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Research on the PID Control Method for Indoor Heating Temperature Based on the Improved Coati Optimization Algorithm

Research on the PID Control Method for Indoor Heating Temper...

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IEEE international conference on Control and robotics Engineering (ICCRE)

作者： Weixin Wang Liqing Geng Genghuang Yang Yang Huo School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing & Intelligent Control Tianjin University of Technology and Education Tianjin China Oumingzhuang Biotechnology (Tianjin) Co. Ltd. Tianjin China

ISBN: (数字)9798350372694

ISBN: (纸本)9798350372700

the proposed solution addresses the issues of high overshoot and long response time in traditional PID control methods for complex nonlinear heating systems with large inertia and pure lag. the Improved Coati Optimization Algorithm (ICOA-PID) introduces an enhanced controller. Firstly, the heating system's primary and secondary piping transfer function models are established. Secondly, the Coati Optimization Algorithm (COA) has been improved in four aspects: the introduction of the chaotic mapping mechanism, nonlinear inertial weighting factors, t-distribution variation, and the coati alarmist mechanism, and the test is carried out using the CEC2022 function set, which performs well in solving most of them in dimension 20; meanwhile, the data are plotted in boxplots. It can be observed that ICOA has both the smallest mean height and the smallest interquartile range (IQR). these verify that the ICOA is able to converge more rapidly, with a greater degree of accuracy and stability than other algorithms. Finally, the simulation experiments were conducted, the step response plot demonstrated that the rise time of the ICOA-PID controller was reduced by 5 seconds in comparison to the pre-improvement period, and by approximately 10 seconds in comparison to the DBO-PID controller. Additionally, the amount of overshoot was reduced by 2% in comparison to the pre-improvement period; the fitness value curves indicate that the fitness value of the ICOA-PID controller is consistently minimized, indicating that it identifies the most optimal set of PID parameters. the error curve exhibits a rapid and pronounced decline, indicating the optimization of parameters to achieve both dynamic responsiveness and static accuracy within the system. the aforementioned results substantiate that the IOCA-PID control methodology is more effective in meeting the indoor thermal demand demands of winter users compared to other algorithmic controllers, and thus possesses certain practical relevance

关键词： PI control Accuracy Heat engines Water heating Transfer functions Stability analysis PD control

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Pilot Misoperation Control Based on L1 Adaptation and INDI methods 16

Pilot Misoperation Control Based on L1 Adaptation and INDI M...

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16th IEEE international conference on Control, automation, robotics and Vision (ICARCV)

作者： Wan, Jin Huang, Dan Song, Lei Ding, Lu Fu, Shan Shanghai Jiao Tong Univ Sch Aeronaut & Astronaut Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781728177090

the pilot's error is one of the important factors affecting flight safety, which may cause serious consequences. this article mainly discusses the continuous operating deviation and sudden large-scale misoperation during the flight process. For the two types of error models, the controllers are designed to reduce the impact after the misoperation occurs, and simulation verification is performed. Simulation results show that the L1 adaptive controller can effectively suppress the impact of continuous operating deviation on control performance and improve flight comfort;the incremental nonlinear dynamic inverse controller can effectively reduce the impact of large misoperation and restore the original flight state.

关键词： Controllers

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Meta-Learning 3D Shape Segmentation Functions

Meta-Learning 3D Shape Segmentation Functions

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international conference on Autonomous Robots and Agents, ICARA

作者： Yu Hao Hao Huang Shuaihang Yuan Yi Fang NYU Abu Dhabi Abu Dhabi UAE

ISBN: (数字)9798350394245

ISBN: (纸本)9798350394252

Previous deep learning methods for 3D shape part segmentation often require extensive labeled training data, which can limit their effectiveness on unfamiliar classes with limited data. To tackle this, we introduce a novel meta-learning strategy that regards the 3D shape segmentation function as a task. By training over a number of 3D part segmentation tasks, our method is capable to learn the prior over the respective 3D segmentation function space which leads to an optimal model that is rapidly adapting to new part segmentation tasks. To implement our meta-learning strategy, we propose two novel modules: meta part segmentation learner and part segmentation learner. During the training process, the part segmentation learner is trained to complete a specific part segmentation task in the few-shot scenario. In the meantime, the meta part segmentation learner is trained to capture the prior from multiple similar part segmentation tasks. Based on the learned information of task distribution, our meta part segmentation learner is able to dynamically update the part segmentation learner with optimal parameters which enable our part segmentation learner to rapidly adapt and have great generalization ability on new part segmentation tasks. We demonstrate that our model achieves superior part segmentation performance with the few-shot setting on the widely used dataset: ShapeNet.

关键词： Metalearning Training Deep learning Adaptation models Solid modeling three-dimensional displays Shape

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Mathematical models and Control methods of Infectious Diseases 5

Mathematical Models and Control Methods of Infectious Diseas...

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5th international conference on automation, Control and robotics Engineering, CACRE 2020

作者： Yang, Yiwen Zhang, Hanrui Business School of Hohai University Hohai University Changzhou China

ISBN: (纸本)9781728198880

In this paper, the application of mathematical models in infectious disease research is reviewed. this paper mainly introduces SIR infectious disease model, SIRS infectious disease model and some methods of infectious disease control based on model. An SIR model based on the 'compartment' model and a SIRS model with standard incidence, vertical infection, continuous inoculation and treatment were established and analyzed. In this paper, the evolution of infectious diseases is illustrated and the effects of different strategies on the control of infectious diseases are compared. © 2020 IEEE.

关键词： Disease control

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Stability investigation and control synthesis of RLC ladder circuits modeled as uncertain spatially interconnected systems*

Stability investigation and control synthesis of RLC ladder ...

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international conference on Control, automation, robotics and Vision (ICARCV)

作者： Bartłomiej Sulikowski Krzysztof Gałkowski Dongdong Zhao Li Xu Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Zielona Góra Poland School of Information Science and Engineering Lanzhou University Lanzhou China Department of Intelligent Mechatronics Akita Prefectural University Akita Japan

ISBN: (纸本)9781665476881

this paper deals with the problem of stability analysis and control scheme synthesis for RLC ladder circuits modeled as two-dimensional $(2D)$ systems, to which class spatially interconnected systems can be associated. this is because in the state-space model more than one indeterminates appear (time - continuous and the coordinates of the node in the structure - discrete). Hence analysis and control synthesis of such systems require developing new results from the systems theory area. As discussed later on due to the finite number of nodes in real systems under consideration, one option (exploited in this paper) for the analysis and synthesis of such systems is embedding temporal and spatial (node to node) dynamics into one 1D, i.e. $n=1$ , model. In this paper, RLC circuits, displayed as a series, i.e. along one spatial (node) indeterminate, constructed with conductances (resistors - R), inductances (L) and capacitors (C), considered are built of electronic elements with values given with some tolerance. this motivates the application of uncertain state-space model with the polytopic type of uncertainty. then, for such a model, the Linear Matrix Inequalities (LMI) based methodology towards stability analysis and controller design methodology are developed. It actually leads to interesting results from the robust control area. the case study proves the correctness of the proposed methods.

关键词： Analytical models Uncertainty Two dimensional displays RLC circuits Interconnected systems Stability analysis State-space methods

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Integration of Convolutional Neural Networks for Real-Time Monitoring of Soil Health in Precision Agriculture

Integration of Convolutional Neural Networks for Real-Time M...

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international conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： Tummapudi Sunil Krishnagandhi Pachiappan S. Senthilrajan Y. Nagendar Renato R. Maaliw C. Pavin Department of CSE Malla Reddy Engineering College Malkajgiri Hyderabad India Electrical and Electronics Engineering Nandha Engineering College Erode Tamil Nadu India Department of Robotics& Automation Rajalakshmi Engineering College Chennai Tamil Nadu India Department of School of Computer Science and Artificial Intelligence SR University Warangal Telangana India Department of CSE Southern Luzon State University Lucban Quezon Philippines Biomedical Engineer YAR Tech Services Hyderabad India

ISBN: (数字)9798350367904

ISBN: (纸本)9798350367911

Convolutional Neural Networks (CNNs) represent a revolutionary breakthrough in improving crop productivity and sustainability when integrated into real-time monitoring systems for soil health in precision agriculture. CNNs are used in a novel way to analyze soil parameters directly from high-resolution photos taken by in-field sensors, such as moisture content, $\mathbf{p H}$ levels, and nutrient concentration. To forecast soil health measures, a CNN model was trained and validated using a collection of soil samples. the model achieved an accuracy rate of approximately $\mathbf{9 2 \%}$. the CNN-based technique shortens the time needed for soil health evaluation by almost $80 \%$ when compared to conventional approaches that involve manual sampling and laboratory analysis, allowing for quick corrective actions in the field. Additionally, more accurate and timely soil health monitoring was found to boost crop output prediction accuracy by $15 \%$. An up to $20 \%$ decrease in the amount of resources used, especially water and fertilizers, can be achieved by using real-time data processing to make educated decisions about irrigation, fertilizing, and pest management. the CNN model offers scalability and adaptability across a range of crop varieties and soil conditions, and it can be easily integrated into current agricultural IoT frameworks. All things considered, using CNNs for soil health monitoring offers an economical and effective way to improve the accuracy and output of contemporary farming methods.

关键词： Precision agriculture Irrigation Accuracy Soil Predictive models Real-time systems Data models Convolutional neural networks Monitoring Farming

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Introducing Shape Prior Module in Diffusion Model for Medical Image Segmentation

Introducing Shape Prior Module in Diffusion Model for Medica...

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IEEE international conference on Mechatronics, robotics and automation (ICMRA)

作者： Zhiqing Zhang Guojia Fan Tianyong Liu Nan Li Yuyang Liu Ziyu Liu Canwei Dong Shoujun Zhou Shenzhen Institute of Advanced Technology University of Chinese Academy of Sciences Shenzhen China College Of Information Science and Engineering Northeastern University (Of Affiliation) Shenzhen China College Of Geosciences Northeast Petroleum University Shenzhen China Department of Computer Science City University of Hong Kong Shenzhen China Shenyang Institute of Automation University of Chinese Academy of Sciences Shenzhen China Faculty of Science and Engineering Chinese Academy of Sciences University of Nottingham Ningbo China Ningbo China College Of Information Science And Engineering Northeastern University (Of Affiliation) Shenzhen China

ISBN: (数字)9798350307535

ISBN: (纸本)9798350307542

Medical image segmentation is critical for diagnosing and treating spinal disorders. However, the presence of high noise, ambiguity, and uncertainty makes this task highly challenging. Factors such as unclear anatomical boundaries, inter-class similarities, and irrational annotations contribute to this challenge. Achieving both accurate and diverse segmentation templates is essential to support radiologists in clinical practice. In recent years, denoising diffusion probabilistic modeling (DDPM) has emerged as a prominent research topic in computer vision. It has demonstrated effectiveness in various vision tasks, including image deblurring, super-resolution, anomaly detection, and even semantic representation generation at the pixel level. Despite the robustness of existing diffusion models in visual generation tasks, they still struggle with discrete masks and their various effects. To address the need for accurate and diverse spine medical image segmentation templates, we propose an end-to-end framework called VerseDiff-UNet, which leverages the denoising diffusion probabilistic model (DDPM). Our approach integrates the diffusion model into a standard U-shaped architecture. At each step, we combine the noise-added image with the labeled mask to guide the diffusion direction accurately towards the target region. Furthermore, to capture specific anatomical a priori information in medical images, we incorporate a shape a priori module. this module efficiently extracts structural semantic information from the input spine images. We evaluate our method on a single dataset of spine images acquired through X-ray imaging. Our results demonstrate that VerseDiff-UNet significantly outperforms other state-of-the-art methods in terms of accuracy while preserving the natural features and variations of anatomy. the generality and validity of our proposed model are confirmed through extensive experiments. By enabling more precise segmentation of anatomical structures, our framew

关键词： Image segmentation Visualization Accuracy Shape Semantics Noise reduction Anatomical structure Diffusion models Probabilistic logic X-ray imaging

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Comparison of Different Flux-Weakening Strategies of AC-Excited Hybrid Excitation Synchronous Motor

Comparison of Different Flux-Weakening Strategies of AC-Exci...

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international conference on Electrical Machines and Systems (ICEMS)

作者： Y. W. Deng K. Wang J. Li T. Wang College of Automation Nanjing University of Aeronautics and Astronautics China

ISBN: (数字)9781665493024

ISBN: (纸本)9781665493031

Compared with permanent magnet synchronous motor (PMSM), hybrid excitation synchronous motor (HESM) adds a set of electric excitation windings, so the controllable excitation current is introduced, which increases the control freedom of the system, and the magnetic field adjustment is convenient and reliable. It is suitable for aerospace, electric vehicles and other occasions. In this paper, a new type of AC-excited hybrid excitation synchronous motor (AC-EHESM) is studied. Firstly, according to the characteristics of the motor, the mathematical model of the motor is built, and the operation limits of the motor are analyzed. On this basis, three different flux-weakening control methods are compared and studied. these three control strategies can widen the operating area of the motor to a certain extent, and do not depend on the motor parameters, and can be applied to other HESM.

关键词： Simulation Windings Air gaps Synchronous motors Permanent magnet motors Mathematical models Hybrid power systems

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Influence of Mutual Inductance on High-Frequency Impedance Characteristics of Six-Phase PMSM under Inter-Turn Short-Circuit Fault

Influence of Mutual Inductance on High-Frequency Impedance C...

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international conference on Electrical Machines and Systems (ICEMS)

作者： Zihang Yuan Minghao Wang Jingang Bai Jiaxuan Huang Ping Zheng School of Electrical Engineering & Automation Harbin Institute of Technology Harbin China

ISBN: (数字)9781665493024

ISBN: (纸本)9781665493031

To improve the ability to identify the inter-turn short-circuit (ITSC) fault, which is one of the most frequent fault types, of six-phase permanent-magnet synchronous machines (PMSMs), the high-frequency impedance of six-phase PMSM under ITSC fault is analyzed with consideration of the mutual inductance characteristics. the model of coupled magnetic circuit between the fault turns and other phases is established, interpreting the characteristic of mutual inductances with different fault turns locations. the high-frequency impedances of both the ITSC fault phase and healthy phases are analyzed, and the impedance decreases of healthy phase caused by mutual inductance are evaluated. Fault diagnosis indicator utilizing the high-frequency current response is designed and the indicator reliabilities of different voltage injection methods are compared.

关键词： Fault diagnosis Inductance Voltage Reliability engineering Mathematical models Circuit faults Impedance

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