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第42届中国控制会议

作者： Bo Yue Yanfang Wang Shibei Xue Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

Simulation of open quantum systems is undoubtedly critical to design of quantum devices and applications of quantum technologies since dynamics of open quantum systems cannot be solved analytically in general. However, the dimension of open quantum systems grows exponentially as the number of their subsystems increases or as involving complicated environments,which reduces the computational efficiency of the simulation. In this paper, we boost numerical simulation of master equations of open quantum systems from several aspects with which the total time and the occupied memory in the simulation are significantly reduced without losing precision. Our method can be applied to the simulation of non-Markovian quantum systems described by an augmented system model as well. We conduct numerical experiments on simulation of a non-Markovian spin *** with the algorithm in a well-known toolbox, QuTiP, our method can take 26.3% time and less memory under fair conditions.

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A Simplified Economic Model Predictive control Algorithm for Soft Constrained system with Changing Economic Criteria

A Simplified Economic Model Predictive Control Algorithm for...

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第34届中国过程控制会议

作者： Xiaowen Qi Shaoyuan Li Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

To improve the economic performance of soft-constrained systems,this paper proposes a new soft-constrained Economic Model Predictive control(EMPC) approach to cope with changes in economic criteria caused by variations in raw material prices,product prices,market fluctuations,disturbances,*** the one hand,terminal states are permitted to be any admissible equilibrium *** the other hand,slack variables for soft constraints are considered in the cost stage to enhance dynamic operation *** ensure the asymptotic stability,the Lyapunov-like stability constraint is ***,the effectiveness of the proposed method is demonstrated by an isothermal stirred-tank reactor process.

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MOSFormer: A Transformer-based Multi-Modal Fusion Network for Moving Object Segmentation

MOSFormer: A Transformer-based Multi-Modal Fusion Network fo...

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

作者： Zike Cheng Hengwang Zhao Qiyuan Shen Weihao Yan Chunxiang Wang Ming Yang Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

3D moving object segmentation (MOS) is vital for autonomous systems, providing essential information for downstream tasks like mapping and localization. However, current MOS methods face challenges due to the limitation of existing datasets, which are sparse in moving objects and limited in scene diversity. Meanwhile, the prevalent methods are projection-based, struggling with the challenge of blurred boundaries. To tackle the dataset issue, we introduce a nuScenes-based MOS dataset, which provides richer scenes and more dynamic instances. To alleviate the boundary blur-ring issue and further improve accuracy and generalizability, we propose a dual-branch multimodal fusion MOS network, MOSFormer. The Transformer structure is incorporated to extract spatio-temporal information better, while image semantic information is utilized to refine the boundaries of moving objects. Finally, experiments on two datasets show that our method achieves state-of-the-art performance, and a mapping experiment with our method confirms its effectiveness in downstream tasks such as mapping and localization.

关键词： Location awareness Three-dimensional displays Autonomous systems Semantics Object segmentation Transformers Real-time systems Data mining Faces Intelligent robots

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PS-Loc: Robust LiDAR Localization with Prior Structural Reference

PS-Loc: Robust LiDAR Localization with Prior Structural Refe...

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

作者： Rui Li Wentao Zhao Tianchen Deng Yanbo Wang Jingchuan Wang Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University Ministry of Education Key Laboratory of System Control and Information Processing Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Prior structural reference like floor plan is readily accessible in indoor scene, which exhibits the potential of improving localization quality without the requirements of a previously-built high-precision map. This paper introduces a novel optimal transport-based framework for prior structural reference-based localization, aiming to improve the robustness for the robot localization. Leveraging the spacial relations of structures, a matching method based on optimal transport theory is proposed and it improves the robustness of matching results in dynamic scene and rapid rotation conditions. Additionally, this paper handles metric inaccuracies in the known structural reference by implementing an prior guided plane adjustment-based updating strategy. This strategy combines prior and observational information to jointly optimize the structural information within a sliding window. The performance of the framework is validated through real-world experiments, demonstrating superior accuracy and robustness to disturbances from dynamic occlusion and rapid rotation compared to common state-of-the-art SLAM and localization methods.

关键词： Location awareness Measurement Laser radar Simultaneous localization and mapping Accuracy Robustness Robot localization Intelligent robots Floors

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Unequal Error Protection Rateless Codes for Spatial Audio Transmission 24

Unequal Error Protection Rateless Codes for Spatial Audio Tr...

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24th IEEE International Conference on Communication Technology, ICCT 2024

作者： Yin, Junpeng Fu, Yusun Huang, Haobo Tang, Jinhui Shanghai Jiao Tong University Ningbo Artificial Intelligence Institute Ningbo China Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai China Ministry of Education of China School of Electronic Information and Electrical Engineering The Key Laboratory of System Control and Information Processing Shanghai China Shanghai Jiao Tong University Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350363760

Spatial audio is an important component of the metaverse. With the rapid increase of the spatial resolution and the number of objects, the data volume of the spatial side information has grown larger. However, the low bit rate transmission of spatial side information in the object-based audio coding methods leads to the low-quality reconstruction of spatial side information with limited bandwidth. To address this issue, this paper constructs a cascade design of spatial audio coding and unequal error protection (UEP) rateless codes. Furthermore, the further protection of specific spatial side information is proposed for different scenarios, which effectively addresses the limitation of traditional spatial audio coding in side information protection. For the situation where the code length K of different importance levels is different, we propose an adaptive degree distribution (ADD), adding K to the selection probability as an influencing factor, which has better performance than other degree distribution for short code length. ADD is used to replace the multiple degree distribution strategy of the traditional unequal error protection scheme, and the block error rate (BER) is reduced nearly 10 times compared with the traditional scheme. © 2024 IEEE.

关键词： Audio signal processing

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Learning-based 3D Reconstruction in Autonomous Driving: A Comprehensive Survey

arXiv

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arXiv 2025年

作者： Liao, Liewen Yan, Weihao Yang, Ming Zhang, Songan Global Institute of Future Technology Shanghai Jiao Tong University Key Labeoratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiao Tong University Key Labeoratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China

Learning-based 3D reconstruction has emerged as a transformative technique in autonomous driving, enabling precise modeling of both dynamic and static environments through advanced neural representations. Despite data augmentation, 3D reconstruction inspires pioneering solution for vital tasks in the field of autonomous driving, such as scene understanding and closed-loop simulation. We investigates the details of 3D reconstruction and conducts a multi-perspective, in-depth analysis of recent advancements. Specifically, we first provide a systematic introduction of preliminaries, including data modalities, benchmarks and technical preliminaries of learning-based 3D reconstruction, facilitating instant identification of suitable methods according to sensor suites. Then, we systematically review learning-based 3D reconstruction methods in autonomous driving, categorizing approaches by subtasks and conducting multi-dimensional analysis and summary to establish a comprehensive technical reference. The development trends and existing challenges are summarized in the context of learning-based 3D reconstruction in autonomous driving. We hope that our review will inspire future researches. Copyright © 2025, The Authors. All rights reserved.

关键词： 3D reconstruction

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Non-Repetitive: A Promising LiDAR Scanning Pattern

Non-Repetitive: A Promising LiDAR Scanning Pattern

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

作者： Angchen Xie Yeqiang Qian Weihao Yan Chunxiang Wang Ming Yang Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

LiDAR is an essential sensor for intelligent vehicles. Recently, LiDARs used in vehicles produced by different companies have significant differences in their scanning patterns. Some vehicles use mechanical and solid-state (repetitive) LiDARs, while others use prism-based (non-repetitive) LiDARs. The scanning pattern of a LiDAR has a profound impact on its scanning performance. To investigate the influence of LiDAR scanning patterns, we created the "Repetitive-or-not" dataset, which is collected simultaneously by LiDARs with both repetitive and non-repetitive scanning patterns in the CARLA simulation environment. Using this dataset, we conducted a comprehensive statistical analysis of the scanning ability of repetitive and non-repetitive LiDARs. Furthermore, we looked into the effects of these two LiDAR scanning patterns on the performance of various 3D object detection algorithms. Finally, we explored the domain gap in the point cloud data produced by repetitive and non-repetitive LiDARs. Through an in-depth investigation of the "Repetitive-or-not" dataset, we have discovered that non-repetitive LiDAR shows great promise. This conclusion is primarily supported by its superior object scanning capabilities.

关键词： Point cloud compression Laser radar Three-dimensional displays Statistical analysis Intelligent vehicles Object detection Companies Robot sensing systems Intelligent robots

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Uncertainty-Aware Reactive control for Signal Temporal Logic with Unknown Obstacles

Uncertainty-Aware Reactive Control for Signal Temporal Logic...

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Asian control Conference

作者： Chen Chen Shaoyuan Li Xiang Yin Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing the Ministry of Education of China Shanghai China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

In this paper, we investigate the challenge of con-trol synthesis for Signal Temporal Logic (STL) specifications within workspaces harboring unknown obstacles. We consider a sensing-based control setting, where robots are equipped with sensors with a limited sensing range to acquire obstacle locations with prior information. The objective is to synthesize a control strategy that maximize the robustness degree of the STL tasks while simultaneously minimizing the probability of collisions with obstacles during its operation. To address this, we present a receding horizon reactive control framework, tackling the problem by solving an uncertainty-aware optimal planning problem at each time instant. A key aspect of our approach is the avoidance of explicit computation of collision probability. Instead, we transform the uncertainty-aware synthesis problem into a non-probabilistic optimization problem, and the results of which still provide probabilistic guarantees. Simulation results are provided to illustrate the effectiveness of our approach.

关键词： Measurement Simulation Transforms Probability Robot sensing systems Probabilistic logic Robustness

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Data-Driven Distributionally Robust Electricity-Hydrogen Trading Considering The Carbon Intensity of Hydrogen Production

Data-Driven Distributionally Robust Electricity-Hydrogen Tra...

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Asian control Conference

作者： Longyan Li Chao Ning Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

This paper proposes a data-driven distributionally robust local electricity-hydrogen market framework, where Hydrogen-based Micro-Grids (HMGs) supply hydrogen to heterogeneous Hydrogen Users (HUs) including hydrogen refueling stations and industrial plants. In this framework, the coordination between HMGs and HUs is cast as a multi-leader multi-follower Stackelberg game. Specifically, HMGs determine an integrated hydrogen-carbon price and carry out electricity trading through a non-cooperative game. Meanwhile, HUs act as followers adjusting hydrogen purchase strategies. Furthermore, the self-dispatching of HMGs and HUs are modeled as distributionally robust optimization problems considering source-load and hydrogen demand uncertainties, respectively. To hedge against these uncertainties, a novel Bayesian nonparametric hybrid ambiguity set is constructed based on local Wasserstein balls and moment information. Finally, a distributed algorithm is developed to solve the market clearing problem. Comparative studies validate that the proposed framework outperforms existing methods, demonstrating a total income improvement of 12.3% and a carbon emission reduction of 11.6%.

关键词： Uncertainty Hydrogen Carbon dioxide Pricing Games Production Power markets

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Accelerated Simulation of Non-Markovian Quantum systems Using Quantum Trajectory

Accelerated Simulation of Non-Markovian Quantum Systems Usin...

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第42届中国控制会议

作者： Yanfang Wang Bo Yue Shibei Xue Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China

Quantum trajectory can be viewed as a numerical simulation method for wavefunctions which consume smaller memories compared to density matrices in master equations. In this paper, we adopt quantum trajectory to simulate the evolution of a non-Markovian quantum system modeled by an augmented system and further use parallel computing to improve *** to the Lindblad master equation solver in QuTiP, it can run more efficiently using less memory. In the example of a8-spin-chain non-Markovian system, it only takes about 0.57% of the memory footprint and 4.12% of the runtime of the solver for the Lindblad master equation.

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