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2024 China automation Congress, CAC 2024

作者： Liang, Xiao Shangguan, Wei Zha, Yuanyuan School of Automation and Intelligence Beijing Jiaotong University Beijing China School of Automation and Intelligence State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing China

ISBN: (纸本)9798350368604

Path planning is a key research focus in the control technology of unmanned systems, such as intelligent vehicles and robots. The conventional A* algorithm suffers from low search efficiency, redundant paths, and impractical solutions;also, the planned path is often too close to obstacles, and the vehicle behavior does not meet realistic dynamics when turning. All of these factors prevent it from being effectively used in practical applications such as the autonomous navigation of intelligent vehicles and robots. In this paper, an improved A* algorithm is proposed. First, the artificial potential field method is introduced to guide the path nodes away from the different level dangerous areas near obstacles to increase the safety of the path. Second, due to the restriction of the vehicle driving direction by lane, a strategy is proposed to constrain the expansion direction of nodes, and the unidirectional A* algorithm is extended to the bidirectional A* algorithm, which improves computational efficiency while meeting the requirements for the forward direction in specific road sections. Finally, redundant point processing strategies and cubic B-spline curves are used to further optimize and smooth the path. Experimental results show that the performance of the improved algorithm is superior to the original algorithm. It shortens the path length, reduces the runtime of the algorithm, eliminates path points that are too close to the edges and sharp curves, and resolves the issue of vehicles driving against the traffic on certain roads, thus achieving significant optimization. © 2024 ieee.

关键词： Robot programming

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‘Parenting the Internet’ App: a Web Guardian for Protecting Neurodiverse Users Online

‘Parenting the Internet’ App: a Web Guardian for Protectin...

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International symposium on computational intelligence and Informatics

作者： Ryan Jones M A Hannan Bin Azhar School of Engineering Technology and Design Canterbury Christ Church University Canterbury United Kingdom

ISBN: (数字)9798350353433

ISBN: (纸本)9798350353440

The rising prevalence of Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) necessitates tailored digital interventions for safeguarding and enhancing the well-being of affected individuals. This paper presents the development and evaluation of a parental control application, ‘Parenting the Internet’ (PTI), designed specifically for individuals with ASD and ADHD. By conducting a comparative analysis of internet usage and safety concerns between neurodiverse and neurotypical participants through detailed questionnaires, the study identifies the unique challenges faced by these groups. Key findings include preferences for specific app features, the importance of a user-friendly interface, and robust security measures. The evaluation highlights strengths in customisation, usability, and scalability while identifying areas for improvement such as educational content expansion and enhanced automation. This research contributes to the development of inclusive digital safety solutions tailored to the needs of neurodiverse users, with implications for broader applications.

关键词： Autism automation Atmospheric measurements Scalability Particle measurements Safety Security Usability Informatics computational intelligence

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Reinforcement Learning-Based Motion Planning for Robotic Manipulators in Smart Industry 15

Reinforcement Learning-Based Motion Planning for Robotic Man...

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15th International Conference on Information and Communication Technology Convergence, ICTC 2024

作者： Cho, Junhyung Jung, Soyi Ajou University Dept. Artificial Intelligence Convergence Network Suwon16499 Korea Republic of Ajou University Dept. Electrical and Computer Engineering Suwon16499 Korea Republic of

ISBN: (纸本)9798350364637

The advent of smart industry, propelled by the inte-gration of digital technologies and automation, has revolutionized manufacturing and industrial processes. Robotics and artificial intelligence (AI) are at the forefront of this transformation, driving extensive research into robotic automation and motion planning. Traditional motion planning algorithms, such as artificial potential fields, bio-inspired heuristics, and sampling-based methods, often falter in complex environments due to their high computational demands and tendency to produce non-optimal solutions. Reinforcement learning (RL) has emerged as a powerful alternative, offering real-time adaptation and optimal decision-making in dynamic settings. This paper reviews the inherent limitations of classical motion planning approaches and explores contemporary trends in RL-based methods, with a focus on their application in smart industry. It highlights the advantages of RL in enhancing adaptability, efficiency, and robustness, particularly in high-dimensional and dynamic environments. Key discussions include the integration of RL with traditional techniques, the extension of RL applications across various domains, and the role of sensor-based approaches in improving motion control. © 2024 ieee.

关键词： Smart manufacturing

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Applications and Experiments on Query-based Object-aware Visual Language Mapping using Frame Division Method in Microcomputers 13

Applications and Experiments on Query-based Object-aware Vis...

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13th International Conference on control, automation and Information Sciences, ICCAIS 2024

作者： Yun, Jun Young Kang, Daeyoel Myeong, Noheun Park, Jongyoon Kim, Pileun Korea Aerospace University Department of Artificial Intelligence Goyang Korea Republic of Korea Aerospace University Department of Autonomous Vehicle Engineering Goyang Korea Republic of

ISBN: (纸本)9798331542047

This paper demonstrates an approach to integrate object-aware map building technique which employs visual language models in microcomputers. This paper addresses the computational challenges of deploying visual language models in resource-constrained environments, such as mobile robots with microcomputers. It is achieved by separating object-aware map building process. The proposed mapping process is divided into 3 stages, data acquisition stage, object-aware map building stage, and inference stage. Experiments are conducted with Turtlebot4 mobile robot with Raspberry Pi microcomputers, to validate its performance in low-powered devices. The result showed 66% of success rate in overall text list, including 60% success rate with input texts with description. This study contributes to mobile robotics by showing that even microcomputers with limited processing power can support object-aware navigation tasks through optimized mapping method. © 2024 ieee.

关键词： Microcomputers

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Secure Storage and Access control for Personal and EEG Data using Blockchain 23

Secure Storage and Access Control for Personal and EEG Data ...

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23rd ieee International symposium on computational intelligence and Informatics, CINTI 2023

作者： Nemes, Gyula Adam Tureczki, Bence Szenes, Katalin Eigner, Gyorgy Óbuda University Physiological Controls Research Center Hungary Biomatics and Applied Artificial Intelligence Institute John von Neumann Faculty of Informatics Óbuda University Hungary Óbuda University Doctoral School of Applied Informatics and Applied Mathematics John von Neumann Faculty of Informatics Bećsi road 96/B Budapest1034 Hungary Institute for Cyber-Physical Systems John von Neumann Faculty of Informatics Óbuda University Bećsi road 96/B Budapest1034 Hungary

ISBN: (纸本)9798350342949

This paper introduces a blockchain-based solution for secure and efficient management of personal and EEG data for research subjects. Our approach separates but interlinks the data to ensure privacy and integrity, with role-based access controls implemented via a Solidity smart contract on the Ethereum blockchain. We integrate the principles of operational excellence to enhance traditional information security methodologies, focusing on a more comprehensive understanding and functionality of data management. Our method offers a secure, efficient, and user-friendly data management system, drawing stakeholders closer to essential professional practices and upholding the values of privacy and integrity. © 2023 ieee.

关键词： Blockchain

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An Approximation Technique for Solving Linear-Quadratic Optimal control Problems Using Chebyshev Polynomials*

An Approximation Technique for Solving Linear-Quadratic Opti...

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2023 ieee International symposium on Product Compliance Engineering - Asia 2023, ISPCE-AS 2023

作者： Wu, Di Xue, Yuanyuan Bai, Yanqin Yu, Changjun Ling, Bingo Wing-Kuen Miao, Zhonghua Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China Shanghai University Department of Mathematics Shanghai200444 China Guangdong University of Technology Faculty of Information Engineering Guangzhou510006 China

ISBN: (纸本)9798350361209

We introduce an innovative numerical method for addressing Linear-Quadratic optimal control problems that come with control constraints. Initially, we reframe the LQ optimal control problem into an unconstrained problem by utilizing the constraint transcription technique. Next, we employ Chebyshev series to approximate both the state and control functions. To bolster the approximation precision, Chebyshev series are further leveraged to approximate the coefficient functions inherent to the linear dynamic system. According to the unique attributes of Chebyshev polynomials, the approximate problem can be seamlessly converted into a corresponding quadratic programming problem. As a result, any feasible solution to the approximate problem guarantees compliance with its dynamic system throughout the complete time horizon. To substantiate the effectiveness of our proposed methodology, we've tested it on a real-world scenario. The computational results underscore that our method outperforms the Chebyshev pseudo-spectral method in terms of approximation accuracy. © 2023 ieee.

关键词： Chebyshev polynomials

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An Adaptive Large Neighborhood Search-Based Task Offloading Approach for Orbit Edge Computing 13

An Adaptive Large Neighborhood Search-Based Task Offloading ...

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13th ieee Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Wang, Zhongxiao Peng, Qinglan Sun, Ruoxiao Wu, Chunrong College of Artificial Intelligence Henan University Zhengzhou475004 China

ISBN: (纸本)9798350361674

The rapid growth of global smart devices has led to a significant demand for computing resources to be sunk to the edge, giving rise to the paradigm of edge computing. Simultaneously, the demand for computational power from users in remote areas, where computing resources are scarce, has driven the emergence and development of the Orbit Edge Computing (OEC) concept. In the context of OEC, users in remote areas can offload computational tasks to edge servers deployed on low-earth orbit satellites through satellite-ground and satellite-satellite communication links, thus overcoming the limitations of ground-based computing and communication infrastructure and providing users in remote areas with low-latency and highly reliable services. However, most existing methods for task offloading in OEC scenarios fail to simultaneously consider the tradeoff between task offloading latency and energy consumption during task processing and lack consideration for task diversity. To address these issues, a Delay and Energy-aware Task Offloading Approach for Orbit Edge Computing, based on Adaptive Large Neighborhood Search (DEA-ALNS), is proposed. This method aims to minimize the weighted task processing cost, taking into account the type of tasks, and introduces specific destruction and repair operators to further improve search efficiency and offloading scheduling quality while minimizing latency. Experimental results based on Walker Delta low-earth orbit satellite constellation and real computational task data demonstrate that compared to the traditional OEC Task Allocation (OEC-TA) method, the proposed DEA-ALNS method can reduce up to 42.22% of the weighted task processing cost and decrease the average latency by 42.46% in heterogeneous OEC scenarios with multiple task sets. © 2024 ieee.

关键词： Energy utilization

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Intention-Aware Decision-Making for Mixed Intersection Scenarios 17

Intention-Aware Decision-Making for Mixed Intersection Scena...

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17th ieee International symposium on Applied computational intelligence and Informatics, SACI 2023

作者： Varga, Balint Yang, Dongxu Hohmann, Soren Institute of Control Systems Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798350321104

This paper presents a white-box intention-aware decision-making for the handling of interactions between a pedestrian and an automated vehicle (AV) in an unsignalized street crossing scenario. Moreover, a design framework has been developed, which enables automated parameterization of the decision-making. This decision-making is designed in such a manner that it can understand pedestrians in urban traffic and can react accordingly to their intentions. That way, a human-like response to the actions of the pedestrian is ensured, leading to a higher acceptance of AVs. The core notion of this paper is that the intention prediction of the pedestrian to cross the street and decision-making are divided into two subsystems. On the one hand, the intention detection is a data-driven, black-box model. Thus, it can model the complex behavior of the pedestrians. On the other hand, the decision-making is a white-box model to ensure traceability and to enable a rapid verification and validation of AVs. This white-box decision-making provides human-like behavior and a guaranteed prevention of deadlocks. An additional benefit is that the proposed decision-making requires low computational resources only enabling real world usage. The automated parameterization uses a particle swarm optimization and compares two different models of the pedestrian: The social force model and the Markov decision process model. Consequently, a rapid design of the decision-making is possible and different pedestrian behaviors can be taken into account. The results reinforce the applicability of the proposed intention-aware decision-making. © 2023 ieee.

关键词： Decision making

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A Bio-Inspired Flapping-Wing Robot With Cambered Wings and Its Application in Autonomous Airdrop

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ieee/CAA Journal of Automatica Sinica 2022年第12期9卷 2138-2150页

作者： Haifeng Huang Wei He Qiang Fu Xiuyu He Changyin Sun School of Intelligence Science and Technology University of Science and Technology BeijingBeijing 100083China Institute of Artificial Intelligence University of Science and Technology BeijingBeijing 100083China IEEE School of Automation Southeast UniversityNanjing 210096 School of Artificial Intelligence Anhui UniversityHefei 230601China

Flapping-wing flight, as the distinctive flight method retained by natural flying creatures, contains profound aerodynamic principles and brings great inspirations and encouragements to drone developers. Though some ingenious flapping-wing robots have been designed during the past two decades, development and application of autonomous flapping-wing robots are less successful and still require further research. Here, we report the development of a servo-driven bird-like flapping-wing robot named USTBird-I and its application in autonomous *** by birds, a camber structure and a dihedral angle adjustment mechanism are introduced into the airfoil design and motion control of the wings, respectively. computational fluid dynamics simulations and actual flight tests show that this bionic design can significantly improve the gliding performance of the robot, which is beneficial to the execution of the airdrop ***, a vision-based airdrop experiment has been successfully implemented on USTBird-I, which is the first demonstration of a bird-like flapping-wing robot conducting an outdoor airdrop mission.

关键词： Autonomous airdrop bionic design bio-inspired robot cambered wing flapping wing

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Human mesh model extraction strategy based on NeRF 7

Human mesh model extraction strategy based on NeRF

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7th International Conference on Computer Information Science and Application Technology, CISAT 2024

作者： Mao, Zhongxi Li, Zhihua HoHai University College of Artificial Intelligence and Automation ChangZhou China

ISBN: (纸本)9798350375107

This paper introduces a human body three-dimensional mesh extraction strategy based on Neural Radiance Fields (NeRF), aiming to address the limitations of existing technologies in acquiring high-quality 3D human body models. Traditional techniques require expensive equipment and specialized setups, while our system is more lightweight and can quickly generate new viewpoint images and editable 3D mesh models with limited computational resources. By combining SMPL-parameterized human body models with NeRF rendering, our system can accurately capture both the shape and appearance of human bodies while allowing for control over the reconstruction process. The paper discusses the key stages of the reconstruction process, such as model training, image rendering, mesh model extraction, and the formulation of loss functions. Experimental results show that our reconstruction system surpasses existing approaches on the People-Snapshot benchmark dataset, particularly in preserving intricate clothing textures. © 2024 ieee.

关键词： 3D reconstruction

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