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检索条件"丛书名=Lecture notes in artificial intelligence,"

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CodeMosaic Patch: Physical Adversarial Attacks Against Infrared Aerial Object Detectors 21st

CodeMosaic Patch: Physical Adversarial Attacks Against Infra...

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21st Pacific Rim International Conference on artificial intelligence

作者： He, Hangwei Wu, Libing Wang, Enshu Wang, Yizhou Zhao, Yu Wuhan Univ Sch Cyber Sci & Engn Wuhan 430072 Peoples R China

ISBN: (纸本)9789819601158;9789819601165

In recent years, drones illegally spy on military bases and steal military secrets, especially in dark scenes. In the face of illegal detection by drones, physical infrared adversarial patches can play a defensive role. Existing methods are either hard to implement physically or lose effectiveness over time. They also overlook that the target may be positioned at various angles. To solve this problem, we design the CodeMosaic Patch (CMP) method for attacks on infrared remote sensing object detectors, which combines remote sensing attacks and infrared attacks to hide non-live targets like vehicles. The CMP utilizes differential evolutionary algorithms to train the patch's structure, texture, size, position, and rotation angle. We use aluminum foil as the reproduction material for infrared patches, successfully concealing the target object from infrared detectors in the real world. Experimental results show that the average digital and physical domain attack success rates (ASR) are 84.2% and 81.02%, respectively. Notably, our CMP can transition from infrared to visible light, achieving a 92.42% ASR and demonstrating cross-modality generalization. This represents the first instance of a patch with cross-modality attack performance being proposed.

关键词： Infrared adversarial attacks Physical adversarial patches Infrared aerial object detectors Cross-modality generalization capabilities

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DaNCES: A Framework for Data-inspired Agent-Based Models of Collective Escape 17th

DaNCES: A Framework for Data-inspired Agent-Based Models of ...

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17th International Conference on Simulation of Adaptive Behavior (SAB)

作者： Papadopoulou, Marina Hildenbrandt, Hanno Hemelrijk, Charlotte K. Swansea Univ Biosci Sch Biosci Geog & Phys Swansea W Glam Wales Univ Groningen Groningen Inst Evolutionary Life Sci Groningen Netherlands

ISBN: (纸本)9783031715327;9783031715334

The collective escape of predators by prey is a classic example of adaptive behavior in animal groups. Across species, prey has evolved a large repertoire of individual evasive maneuvers they can use to evade predators. With recent technological advances, more empirical data of collective escape is becoming available, and a large variation in the collective dynamics of different species is apparent. However, given the complexity of patterns of collective escape, we are still lacking the tools to understand their emergence. Computational models that can link rules of individual behavior to patterns of collective escape are needed, but species-specific motion and escape characteristics that will allow the link between behavior and eco-evolutionary dynamics of a given species are rarely included in agent-based models of collective behavior. Here, to tackle this challenge, we introduce a framework that uses individual-based state machines to model spatio-temporal dynamics of collective escape. A synthetic agent in our framework can switch its behavior between 'flocking' with different coordination specifics (e.g., quicker interactions when vigilant) and 'escape' with various maneuvers through a dynamic Markov-chain, depending on its local information (e.g., its relative position to the predator). A user can compose a new agent-based model adjusted to empirical data by choosing a set of states (which includes rules of motion, interaction, and escape), their temporal order, and a detailed parameterization. The flexibility and structure of our software allows substantial changes in a model with very minimal code alterations, showing great potential for future use to identify the underlying mechanisms of collective escape across species and ecological contexts.

关键词： Collective escape Agent-based modeling Predator-prey interactions

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Abstract Dialectical Frameworks are Boolean Networks 17th

Abstract Dialectical Frameworks are Boolean Networks

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17th International Conference on Logic Programming and Non-monotonic Reasoning

作者： Heyninck, Jesse Knorr, Matthias Leite, Joao Open Univ Heerlen Netherlands Univ Cape Town Cape Town South Africa NOVA Univ NOVA LINCS Lisbon Portugal

ISBN: (纸本)9783031742088;9783031742095

The Abstract dialectical frameworks are a unifying model of formal argumentation, where argumentative relations between arguments are represented by assigning acceptance conditions to atomic arguments. Their generality allows them to cover a number of different approaches with varying forms of representing the argumentation structure. Boolean regulatory networks are used to model the dynamics of complex biological processes, taking into account the interactions of biological compounds, such as proteins or genes. These models have proven highly useful for comprehending such biological processes, allowing to reproduce known behaviour and testing new hypotheses and predictions in silico, for example in the context of new medical treatments. While both these approaches stem from entirely different communities, it turns out that there are striking similarities in their appearence. In this paper, we study the relation between these two formalisms revealing their communalities as well as their differences, and introducing a correspondence that allows to establish novel results for the individual formalisms.

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An MPC-Based Control Scheme for an Aircraft Towing and Taxiing System Under Uncertainties 17th

An MPC-Based Control Scheme for an Aircraft Towing and Taxii...

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17th International Conference on Intelligent Robotics and Applications

作者： Huang, Weining Xu, Pengjie Zhao, Tianrui Zhang, Wei Zhao, Yanzheng Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Civil Aviat Univ China Sch Aeronaut Engn Tianjin 300300 Peoples R China

ISBN: (纸本)9789819607822;9789819607839

The market of the civil aviation industry has witnessed great growth in recent years and it is estimated to continue to boom in the future. However, at the same time, environmental issues are emerging. To mitigate the conflict, in this paper, a control system based on adaptive MPC and extended Kalman filter is designed for the aircraft towing and taxiing (ATT) system in the application of an autonomous tractor in the airport. First, the kinematics model of the ATT system is established, and then, the model is linearized and discretized for the design of the adaptive MPC controller. Afterward, the cost function is designed considering the trajectory tracking accuracy and passenger comfort simultaneously under safe operation conditions. Several constraints including hitch angle constraints and constraints on control inputs and their relative variables are designed to meet the system requirements. The extended Kalman filter is utilized in the control system for counteracting the potential uncertainties. Finally, simulations in two scenarios are conducted to verify the ability of the designed control system to track the reference trajectory and control inputs while resisting uncertainties. The results demonstrate the robustness and effectiveness in operation under uncertainties.

关键词： Adaptive MPC Extended Kalman Filter Constraints Uncertainties

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Impact of Parent Selection Operator on the FDEA Algorithm 34th

Impact of Parent Selection Operator on the FDEA Algorithm

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34th Brazilian Conference on Intelligent Systems

作者： de Oliveira, Joao Pedro A. Castro, Olacir R., Jr. Univ Fed Acre Rio Branco AC Brazil

ISBN: (纸本)9783031790317;9783031790324

Many-Objective Optimization Problems (MaOPs) present a significant challenge due to the increased complexity associated with optimizing more than three conflicting objectives. Traditional Pareto-based algorithms often struggle to scale effectively with the number of objectives, leading researchers to explore alternative approaches. This study investigates the impact of parent selection strategies on the performance of the Fuzzy Decomposition-Based Multi/Many-Objective Evolutionary Algorithm (FDEA). The FDEA uses a fuzzy decomposition approach to divide a MaOP into subproblems, each solved individually to improve the adaptability and precision of solutions. The study compares the FDEA with three selection methods: binary tournament based on Pareto dominance, binary tournament using crowding distance, and a combination of Pareto dominance and crowding distance. Empirical evaluations were conducted using the DTLZ and WFG benchmark problem sets, with 2, 3, 5, 8, 10, and 15 objectives. The results indicate that incorporating quality indicators into the selection process improves the efficiency and effectiveness of the FDEA, especially in high-dimensional optimization scenarios. However, no variant was superior in all contexts. The study highlights the potential for methodological advances in Indicator-Based Mating Selection, emphasizing the need for robust and scalable algorithms capable of handling the complexities of MaOPs.

关键词： Indicator-Based Mating Selection Many-Objective Parent Selection Strategies

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Context-Aware Structural Adaptive Graph Neural Networks 21st

Context-Aware Structural Adaptive Graph Neural Networks

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21st Pacific Rim International Conference on artificial intelligence

作者： Chen, Jiakun Xu, Jie Hu, Jiahui Qiao, Liqiang Wang, Shuo Huang, Feiran Li, Chaozhuo Beijing Foreign Studies Univ Sch Informat Sci & Technol Beijing Peoples R China China Mobile Commun Grp Shandong Co Ltd Weihai Branch Weihai Peoples R China Jinan Univ Coll Informat Sci & Technol Coll Cyber Secur Guangzhou Peoples R China Beijing Univ Posts & Telecommun Key Lab Trustworthy Distributed Comp & Serv MoE Beijing Peoples R China

ISBN: (纸本)9789819601158;9789819601165

Graph-based data structures are prevalent in various real-world applications, for example, protein molecules and social connection networks, necessitating effective representation learning techniques. Graph Neural Networks (GNNs) have demonstrated significant advancements in tasks like node classification and social network analysis through recursive information aggregation. However, current GNN approaches are predominantly static, lacking adaptability to specific graph structures. Inspired by Neural Architecture Search (NAS) in designing dataset-specific architectures, we propose Context-Aware Structure Adaptive Graph Neural Networks (CAS-GNN). This framework is capable of automatically selecting the appropriate aggregator for each node which is determined by both node attributes and local contextual information. The selection is formulated as the Markov Decision Process (MDP) optimized via Deep-Q-Network (DQN) training. Our contributions include a flexible framework incorporating various aggregators for individual nodes based on their attributes and local context, improved performance through node-specific aggregator selection, and extensive experimental validation demonstrating the effectiveness of CAS-GNN on multiple real-world datasets.

关键词： Graph Neural Networks Node Classification Deep Reinforcement Learning

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Sensorless Safe Interaction Method for Novel Tendon-Driven SuperLimb Based on Dynamic Parameter Identification 1

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17th International Conference on Intelligent Robotics and Applications

作者： Zhang, Qinghua Li, Yuancheng Jing, Hongwei Sun, Kerui Li, Xianglong Zhao, Sikai Li, Lele Ju, Haotian Wang, Ziqi Zheng, Tianjiao Zhao, Jie Zhu, Yanhe Harbin Inst Technol State Key Lab Robot & Syst Harbin 150000 Peoples R China

ISBN: (数字)9789819607921

ISBN: (纸本)9789819607914;9789819607921

Supernumerary Robotic Arms (SuperLimb) are new types of wearable robots designed for human operation augmentation by working closely with the human limb. As a special collaborator of the wearer, the probability of accidental collision is greatly increased, thus posing a formidable challenge to the safety of humans. To address this issue, this paper proposes a sensorless interaction method based on dynamic parameter identification greatly increases the security guarantee between human and SuperLimb. To improve the identification accuracy of the dynamic system, a novel dynamic identification model considering the flexible elastic deformation of tendons is first derived. Subsequently, the detailed excitation trajectory design and optimization are presented. Then, the identification experiment is conducted on the SuperLimb. The experiment results show that the proposed approach with considering the influence of tendon can improve the accuracy of model estimation and the identified dynamic parameters are accurate. Finally, the application experiment is successfully applied in the human-SuperLimb system indicating that the proposed method is useful for increasing the security guarantee between human and SuperLimb.

关键词： Tendon-driven Supernumerary Robotic Arms Coupling dynamics Dynamic parameter identification Sensorless safe interaction

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Layout Optimization of a Heterogeneous Multi-robot System for Mirror Milling 17th

Layout Optimization of a Heterogeneous Multi-robot System fo...

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17th International Conference on Intelligent Robotics and Applications

作者： Huang, Chenghao Chen, Kun Shan, Xianlei Xu, Peng Li, Bing Harbin Inst Technol Shenzhen Sch Mech Engn & Automat Shenzhen 518055 Peoples R China Tianjin Univ State Minist Educ Key Lab Mech Mech & Equipment Design Tianjin 300072 Peoples R China

ISBN: (纸本)9789819607884;9789819607891

Layout optimization is essential to build a multi-robot system. Layout parameters affect the cooperation efficiency and the utilization rate of the workspace. This paper conducts layout optimization of a dual-robot system for mirror milling. It contains a hybrid robot for milling and a serial robot for supporting during the machining of thin-walled parts. The milling robot and supporting robot are modeled geometrically, and the reachable workspaces of the two robots are obtained with the help of forward and inverse kinematics. An algorithm for solving the maximum regular workspace based on a nonlinear programming method is developed, which does not require complex mathematical derivation and is universal for both concave and convex polygons. The manipulability analysis of the serial robot at the support end is carried out, and the area with low manipulability is eliminated from the reachable space. A layout optimization method that involves the reachability, workspace regularity, and manipulability of the robot is proposed and validated by theoretical analyses.

关键词： Layout optimization Dual-robot system Mirror milling

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A Multi-level Semantics Formalism for Multi-Agent Microservices 34th

A Multi-level Semantics Formalism for Multi-Agent Microservi...

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34th Brazilian Conference on Intelligent Systems

作者： Panisson, Alison R. Farias, Giovani P. Fed Univ Santa Catarina UFSC Dept Comp DEC Ararangua Brazil

ISBN: (纸本)9783031790287;9783031790294

Operational semantics is a fundamental approach to the formalisation of programming languages and almost a standard when it comes to agent-oriented programming languages. It helps ensure the correctness of interpreters, facilitates their implementation, and supports proofs of important properties. However, in the literature, there are few attempts of formalising multi-level operational semantics for multi-agent systems which allows the formalisation of all levels of abstraction in those systems. Also, recently, authors have started to discuss a new approach to build multi-agent systems known as multi-agent microservices, arguing that microservices represent a potential point of convergence between modern software engineering and multi-agent systems. We agree that microservices could be a useful approach to think of multi-agent systems and, in this paper, we propose a multi-level semantics to formalise this new approach to build multi-agent systems based on the abstraction of microservices. We not only introduce a template for those formalisation but we also show how our operational semantics style promotes desired characteristics of modularity, reusability, and a clear specification of shared communication artifacts in multi-agent microservices.

关键词： Multi-agent Systems Microservices Multi-level Semantics

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MFap: Multi-view Feature Map for Visual Localization 17th

MFap: Multi-view Feature Map for Visual Localization

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17th International Conference on Intelligent Robotics and Applications

作者： Deng, Jiaxin Yang, Xu Zheng, Suiwu Gu, Nannan Liu, Chuankai Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100190 Peoples R China Huizhou Zhongke Adv Mfg Ltd Co Huizhou 516000 Peoples R China Capital Univ Econ & Business Sch Stat Beijing 100070 Peoples R China Beijing Aerosp Control Centera Beijing 100094 Peoples R China

ISBN: (纸本)9789819607730;9789819607747

The core of traditional visual localization methods is local feature matching. However, local feature matching relies on the similarity of fine details and structures in local content. In practical applications, there are often scenarios where the difference in camera poses is too large, causing the repeated regions between images to almost disappear and making it impossible to obtain enough similar local features. An example of this is ground-to-aerial view matching. In such cases, localization based on local feature matching often fails to achieve precise positioning. Images from different viewpoints have distinct characteristics: ground views usually have higher resolution and clearer details but a smaller field of view, presenting more specific content information;aerial views have lower resolution but contain rich semantic and scene structure information. These complementary characteristics from different perspectives are advantageous. Therefore, for scenarios with significant viewpoint differences, this paper proposes a ground-to-aerial multiview fusion method based on existing scene regression techniques. The method leverages known camera poses to fuse multi-view images into a Bird's Eye View (BEV) feature map that contains rich scene information. This provides a global top-down perspective to help understand and analyze objects and structures in the environment. Matching is performed in the BEV feature space, directly regressing to obtain the pose of the query image, thus achieving precise localization. Extensive experiments have been conducted on this method, comparing it with current local feature matching methods. Results show that in scenarios with large view-point differences, this method surpasses traditional localization methods, achieving precise and robust localization.

关键词： Visual localization Feature fusion Self supervision

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