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2025 Design, automation and Test in Europe Conference, DATE 2025

作者： Sun, Penghao Zheng, Shengan Deng, Kaijiang Wang, Guifeng Pu, Jin Yang, Jie Yuan, Maojun Zhu, Feng Li, Shu Huang, Linpeng Shanghai Jiao Tong University China MoE Key Lab of Artificial Intelligence Ai Institute Shanghai Jiao Tong University China Alibaba Group China

ISBN: (纸本)9783982674100

computational SSDs implement the in-storage computing (ISC) paradigm and benefit applications by taking over I/O-intensive tasks from the host. Existing works have proposed various frameworks aiming at easy access to ISC functionalities, and among them generic frameworks with file-based abstractions offer better usability. However, since intermediate output by ISC tasks may leave files in a dirty state, concurrent access to and the integrity of file data should be properly managed, which has not been fully addressed. In this paper, we present TxISC, a generic ISC framework that coordinates the host kernel and device firmware to offer a versatile file-based programming model. Under the hood, TxISC turns each invocation of an ISC task into a transaction with full ACID guarantee, fully covering concurrency control and data protection. TxISC implements transactions at low cost by leveraging the out-of-place write characteristic of NAND flash. Evaluation on full-stack hardware shows that transactions incur almost no runtime performance penalty compared with existing ISC architectures. Application case studies demonstrate that the programming model of TxISC can be used to offload complex logic and deliver significant speedup over host-only solutions. © 2025 EDAA.

关键词： Concurrency control

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A Geometric Folding Pattern for Robot Coverage Path Planning

A Geometric Folding Pattern for Robot Coverage Path Planning

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ieee International Conference on Robotics and automation (ICRA)

作者： Zhu, Lifeng Yao, Shuai Li, Boyang Song, Aiguo Jia, Yiyang Mitani, Jun Southeast Univ State Key Lab Bioelect Jiangsu Key Lab Remote Measurement & Control Sch Instrument Sci & Engn Dhaka Bangladesh Univ Tsukuba Tsukuba Ibaraki Japan China Jiliang Univ Hangzhou Peoples R China Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9781728190778

Conventional coverage path planning algorithms are mainly based on the zigzag and spiral patterns or their combinations. The traversal order is limited by the linear or inside-outside manner. We propose a new set of coverage patterns induced from geometric folding operations, called the geometric folding pattern, to make coverage paths with more flexible traversal order. We study the modeling and parameterization of the geometric folding patterns. Then, a sampling operator is introduced. Based on the computational tools, we demonstrate the application of the proposed patterns in designing coverage paths. We show that the simple geometric folding patterns are flexible and controllable, which enables more choices for the coverage path planning problem.

关键词： Spirals automation Conferences computational modeling Tools Aerospace electronics Data structures

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Equality Constrained Linear Optimal control With Factor Graphs

Equality Constrained Linear Optimal Control With Factor Grap...

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ieee International Conference on Robotics and automation (ICRA)

作者： Yang, Shuo Chen, Gerry Zhang, Yetong Choset, Howie Dellaert, Frank Carnegie Mellon Univ Robot Inst Pittsburgh PA 15213 USA Carnegie Mellon Univ Dept Mech Engn Pittsburgh PA 15213 USA Georgia Inst Technol Inst Robot & Intelligent Machines Atlanta GA 30332 USA

ISBN: (纸本)9781728190778

This paper presents a novel factor graph-based approach to solve the discrete-time finite-horizon Linear Quadratic Regulator problem subject to auxiliary linear equality constraints within and across time steps. We represent such optimal control problems using constrained factor graphs and optimize the factor graphs to obtain the optimal trajectory and the feedback control policies using the variable elimination algorithm with a modified Gram-Schmidt process. We prove that our approach has the same order of computational complexity as the state-of-the-art dynamic programming approach. Furthermore, current dynamic programming approaches can only handle equality constraints between variables at the same time step, but ours can handle equality constraints among any combination of variables at any time step while maintaining linear complexity with respect to trajectory length. Our approach can be used to efficiently generate trajectories and feedback control policies to achieve periodic motion or repetitive manipulation.

关键词： Regulators Heuristic algorithms Conferences Optimal control Process control Trajectory Feedback control

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Real-Time Adaptive Safety-Critical control with Gaussian Processes in High-Order Uncertain Models

Real-Time Adaptive Safety-Critical Control with Gaussian Pro...

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ieee International Conference on Robotics and automation (ICRA)

作者： Yu Zhang Long Wen Xiangtong Yao Zhenshan Bing Linghuan Kong Wei He Alois Knoll Department of Informatics Technical University of Munich Germany Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macau China School of Intelligence Science and Technology University of Science and Technology Beijing Beijing China Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of Education University of Science and Technology Beijing Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper presents an adaptive online learning framework for systems with uncertain parameters to ensure safety-critical control in non-stationary environments. Our approach consists of two phases. The initial phase is centered on a novel sparse Gaussian process (GP) framework. We first integrate a forgetting factor to refine a variational sparse GP algorithm, thus enhancing its adaptability. Subsequently, the hyperparameters of the Gaussian model are trained with a specially compound kernel, and the Gaussian model’s online inferential capability and computational efficiency are strengthened by updating a solitary inducing point derived from newly samples, in conjunction with the learned hyperparameters. In the second phase, we propose a safety filter based on high order control barrier functions (HOCBFs), synergized with the previously trained learning model. By leveraging the compound kernel from the first phase, we effectively address the inherent limitations of GPs in handling high-dimensional problems for real-time applications. The derived controller ensures a rigorous lower bound on the probability of satisfying the safety specification. Finally, the efficacy of our proposed algorithm is demonstrated through real-time obstacle avoidance experiments executed using both simulation platform and a real-world 7-DOF robot.

关键词： Adaptation models Adaptive systems Uncertainty computational modeling Gaussian processes Real-time systems Safety

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Procedural Content Generator for Generating a 3D Graphical Representation of the River Model

Procedural Content Generator for Generating a 3D Graphical R...

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International symposium on Applied Machine intelligence and Informatics (SAMI)

作者： Alžbetá Sklenáriková Branislav Madoš Norbert Ádám Heidar Khorshidiyeh Peter Poprík Lukáš Tornaščík Department of Computers and Informatics Faculty of Electrical Engineering and Informatics Technical University of Ko išce Košice Slovakia

ISBN: (数字)9798350379365

ISBN: (纸本)9798350379372

This work deals with procedural content generation, specializing in content generation in the fields of computer graphics and computer games. Even more precisely, it deals with the procedural generation of three-dimensional polygonal surface models of rivers. In the introductory part, the paper provides an overview of related procedural content generation principles using noise generating functions and more complex simulation techniques. Then, it presents a within this work designed algorithm for the procedural generation of a river model by creating its bed using the designed concept of control tiles, which allow controlling the direction and shape of the river. The generator's goal is to provide a tool for creating river models that can be integrated into the environment of 3D computer games.

关键词： Video games Solid modeling Procedural generation Three-dimensional displays Shape computational modeling Computer graphics Generators Real-time systems Rivers

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computationally Expensive High-Dimensional Multiobjective Optimization via Surrogate-Assisted Reformulation and Decomposition

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ieee Transactions on Evolutionary Computation 2024年 1-1页

作者： Pan, Linqiang Lin, Jianqing Wang, Handing He, Cheng Tan, Kay Chen Jin, Yaochu School of Artificial Intelligence and Automation Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China School of Artificial Intelligence Xidian University Xi’an China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China Department of Computing The Hong Kong Polytechnic University Hong Kong Hong Kong School of Engineering Trustworth and General Artificial Intelligence Laboratory Westlake University Hangzhou China

In recent decades, various surrogate-assisted evolutionary algorithms (SAEAs) have been proposed to solve computationally expensive multiobjective optimization problems (EMOPs). Nevertheless, designing an SAEA to handle high-dimensional EMOPs and balance convergence, diversity, and computational complexity remains challenging. Here, we propose a two-phase SAEA (TP-SAEA), which follows the idea of convergence first and diversity second, for solving high-dimensional EMOPs. In Phase I, a surrogate-assisted problem reformulation method is proposed to fast-track the Pareto optimal set in association with some reference solutions. Specifically, the high-dimensional EMOP is reformulated into an expensive single-objective one with low-dimensional decision space. Then, the surrogate-assisted optimization is utilized to obtain well-converged solutions. In Phase II, the high-dimensional EMOP is decomposed into two subproblems to explore subregions of the decision space that can effectively promote the diversity of the solutions. The two subproblems are optimized independently via surrogate-assisted optimization, aiming to push the population towards different regions of the Pareto optimal front. Experiments are conducted on EMOPs with 100 to 500 decision variables compared with four state-of-the-art SAEAs. The proposed TP-SAEA obtains well-converged and diverse solutions with only 509 real function evaluations. Moreover, its superiority is examined in six real-world instances with up to 12,000 decision variables. ieee

关键词： Iron

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Approximate Solutions to a Class of Reachability Games

Approximate Solutions to a Class of Reachability Games

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ieee International Conference on Robotics and automation (ICRA)

作者： Fridovich-Keil, David Tomlin, Claire J. Stanford Univ Dept Aeronaut & Astronaut Stanford CA 94305 USA Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA USA

ISBN: (纸本)9781728190778

In this paper, we present a method for finding approximate Nash equilibria in a broad class of reachability games. These games are often used to formulate both collision avoidance and goal satisfaction. Our method is computationally efficient, running in real-time for scenarios involving multiple players and more than ten state dimensions. The proposed approach forms a family of increasingly exact approximations to the original game. Our results characterize the quality of these approximations and show operation in a receding horizon, minimally-invasive control context. Additionally, as a special case, oar center dot method reduces to local gradient-based optimization in the single-player (optimal control) setting, for which a wide variety of efficient algorithms exist.

关键词： automation Conferences Optimal control Games Approximation algorithms Real-time systems computational efficiency

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A Simplified Variant for Graph Convolutional Network Based Knowledge Graph Completion Model 8

A Simplified Variant for Graph Convolutional Network Based K...

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8th International Conference on Data Science in Cyberspace, DSC 2023

作者： Wang, Yashen Li, Qiang Zhang, Yi Zhang, Xuecheng Ju, Zhuoya Sun, Jian Beijing China Scientific and Technological Innovation Center of Ari Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Cetc Academy of Electronics and Information Technology Group Co. Ltd. Beijing China Khoury College of Computer Science Northeastern University United States Scientific and Technological Innovation Center of Ari Beijing China Qi An Xin Technology Group Inc. Beijing China

ISBN: (纸本)9798350331035

Knowledge graphs (KGs) serve as useful resources for various applications including machine learning, data mining, and artificial intelligence. Knowledge Graph Completion (KGC) aims at reasoning over known (observed) facts and infer the missing (unobserved) relationships, to improve KG's coverage. Many recent works have laid stress on leveraging Graph Convolutional Networks (GCNs) for KGC task, which obtain good representation learning ability for graph-structured data, and have achieved satisfactory results. However, GCN-based researches continue to improve these lines of models by introducing an increasingly complex feature space. Especially, the hyper-parameter space of conventional GCN-based KGC model is too huge, resulting in low computational efficiency and excessive storage pressure. To overcome this problem, this paper investigates a simplified and generic variant for GCN-based KGC model, and shows that simple changes in the architecture of the underlying architecture (with a Subtraction Operator and an Addition Operator), can compte with state-of-the-art GCN-based models. Therefore, this paper proposes a easy-to-accomplish plug-in unit, which could be loaded into any current GCN-based KGC architectures, and help them maximize the maintenance of native model's original performance while significantly reducing parameter scale. © 2023 ieee.

关键词： Graph Convolutional Network Knowledge Graph Knowledge Graph Completion Representation Learning

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A Data-Driven Approach for the Simultaneous Stochastic Optimization of Mining Complexes 19

A Data-Driven Approach for the Simultaneous Stochastic Optim...

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19th IFAC symposium on control, Optimization and automation in Mining, Mineral and Metal Processing (MMM)

作者： Yaakoubi, Yassine Dimitrakopoulos, Roussos McGill Univ Dept Min & Mat Engn COSMO Stochast Mine Planning Lab 3450 Univ St Montreal PQ Canada Univ Montreal GERAD Res Grp Decis Anal Andre Aisenstadt Bldg 2920Chemin Tour Montreal PQ Canada

The simultaneous stochastic optimization of mining complexes (SSOMC) is a large-scale stochastic combinatorial optimization problem that simultaneously manages the extraction of materials from multiple mines and their processing using interconnected facilities to generate a set of finished products while taking into account geological uncertainty to manage the associated risk. To address the need for self-managed solution approaches that are able to tackle large-scale instances without resorting to aggregation, this work proposes a data-driven framework for heuristic scheduling in a fully self-managed hyper-heuristic to solve the SSOMC. The proposed hyper-heuristic selects the heuristic (perturbation) to be applied in a self-adaptive manner using state-of-the-art reinforcement learning methods to efficiently explore which local search is best suited for a particular search point. Experiments on real-world mining complexes show a significant reduction in the computational time by 30-45%. Copyright (C) 2022 The Authors.

关键词： Artificial intelligence Reinforcement learning Mining complexes Stochastic optimization control and optimization Mining operations

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Hilbert Fractal-based HMS Improves the Efficiency of Wireless Power Transfer System 14

Hilbert Fractal-based HMS Improves the Efficiency of Wireles...

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14th International symposium on computational intelligence and Design, ISCID 2021

作者： Tang, Fuhong Fan, Xingming Su, Binhua Zhang, Haonan Zhang, Xin Guilin University of Electronic Technology Department of Electrical Engineering and Automation Guilin China

ISBN: (纸本)9781665438568

To further improve the power efficiency of wireless power transfer(WPT) systems, a hybrid metamaterial slab (HMS) consisting of the 3rd-order Hilbert fractal spiral resonator with magnetic permeability tending to 0 and -1 is proposed. The HMS is applied to a WPT system with an operating frequency of 6.78 MHz. The effect of the Hilbert fractal-based hybrid metamaterial on the WPT system is explored through theoretical analysis and simulation verification. The simulation results show that the incorporation of the Hilbert fractal-based HMS can improve the power efficiency of the WPT system with a transmission distance of 0.4m by 17.57%. © 2021 ieee.

关键词： Fractals

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