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Continuity Scaling: A Rigorous Framework for Detecting and Quantifying Causality Accurately

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Research 2022年第4期2022卷 137-146页

作者： Xiong Ying Si-Yang Leng Huan-Fei MaD Qing Nie Ying-Cheng Lai Wei Lin School of Mathematical Sciences SCMSand SCAMFudan UniversityShanghai 200433China Research Institute for Inteligent Complex Systems CCSBand LCNBIFudan UniversityShanghai 200433China State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain ScienceFudan UniversityShanghai 200032China Institute of AI and Robotics Academy for Engineering and TechnologyFudan UniversityShanghai 200433China School of Mathematical Sciences Soochow UniversitySuzhou 215006China Department of Mathematics Department of Developmental and Cll BiologyAnd NSF-Simons Center for Multiscale Cell Fate ResearchUniversity of CaliforniaIrvineCA 92697-3875USA School of Electrical ComputerAnd Energy EngineeringArizona State UniversityTempeArizona 85287-5706USA Shanghai Artificial Intelligence Laboratory Shanghai 200232China

Data-based detection and quantification of causation in complex,nonlinear dynamical systems is of paramount importance to science,engineering,and *** by the widely used methodology in recent years,the cross-map-based techniques,we develop a general framework to advance towards a comprehensive understanding of dynamical causal mechanisms,which is consistent with the natural interpretation of *** particular,instead of measuring the smoothness of the cross-map as conventionally implemented,we define causation through measuring the scaling law for the continuity of the investigated dynamical system *** uncovered scaling law enables accurate,reliable,and eficient detection of causation and assessment of its strength in general complex dynamical systems,outperforming those existing representative *** continuity scaling-based framework is rigorously established and demonstrated using datasets from model complex systems and the real world.

关键词： dynamical scaling continuity

Designing Online Multiplayer Games with Haptically and Virtually Linked Tangible Robots to Enhance Social Interaction in Therapy

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Designing Online Multiplayer Games with Haptically and Virtu...

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Arzu Guneysu Ozgur Hala Khodr Mehdi Akeddar Michael Roust Pierre Dillenbourg Computer Human Interaction in Learning and Instruction Lab (CHILI) EPFL Lausanne Switzerland Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781728188591

ISBN: (纸本)9781665406802

The social aspects of therapy and training are important for patients to avoid social isolation and must be considered when designing a platform, especially for home-based rehabilitation. We proposed an online version of the previously proposed tangible Pacman game for upper limb training with haptic-enabled tangible Cellulo robots. Our main objective is to enhance motivation and engagement through social integration and also to form a gamified multiplayer rehabilitation at a distance. Thus, allowing relatives, children, and friends to connect and play with their loved ones while also helping them with their training from anywhere in the world. As well as connecting therapists to their patients through haptically linking capabilities. This is especially relevant when there are social distancing measures which might isolate the elderly population, a majority of all rehabilitation patients.

关键词： Training Pediatrics Sociology Medical treatment Games Human factors Social factors

TS-CGNet: Temporal-Spatial Fusion Meets Centerline-Guided Diffusion for BEV Mapping

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arXiv 2025年

作者： Hong, Xinying Li, Siyu Zeng, Kang Shi, Hao Peng, Bomin Yang, Kailun Li, Zhiyong The College of Computer Science and Electronic Engineering Hunan University Changsha410082 China The School of Robotics The National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University Changsha410082 China The State Key Laboratory of Extreme Photonics and Instrumentation Zhejiang University Hangzhou310027 China

Bird’s Eye View (BEV) perception technology is crucial for autonomous driving, as it generates top-down 2D maps for environment perception, navigation, and decision-making. Nevertheless, the majority of current BEV map generation studies focusing on visual map generation lack depth-aware reasoning capabilities. They exhibit limited efficacy in managing occlusions and handling complex environments, with a notable decline in perceptual performance under adverse weather conditions or low-light scenarios. Therefore, this paper proposes TS-CGNet, which leverages Temporal-Spatial fusion with Centerline-Guided diffusion. This visual framework, grounded in prior knowledge, is designed for integration into any existing network for building BEV maps. Specifically, this framework is decoupled into three parts: Local mapping system involves the initial generation of semantic maps using purely visual information;The Temporal-Spatial Aligner Module (TSAM) integrates historical information into mapping generation by applying transformation matrices;The Centerline-Guided Diffusion Model (CGDM) is a prediction module based on the diffusion model. CGDM incorporates centerline information through spatial-attention mechanisms to enhance semantic segmentation reconstruction. We construct BEV semantic segmentation maps by our methods on the public nuScenes and the robustness benchmarks under various corruptions. Our method improves 1.90%, 1.73%, and 2.87% for perceived ranges of 60×30m, 120×60m, and 240×60m in the task of BEV HD mapping. TS-CGNet attains an improvement of 1.92% for perceived ranges of 100×100m in the task of BEV semantic mapping. Moreover, TS-CGNet achieves an average improvement of 2.92% in detection accuracy under varying weather conditions and sensor interferences in the perception range of 240×60m. The source code will be publicly available at https://***/krabs-H/TS-CGNet. Copyright © 2025, The Authors. All rights reserved.

关键词： Decision making

Choosing a Suitable Requirement Prioritization Method: A Survey

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arXiv 2024年

作者： Alhenawi, Esraa Awawdeh, Shatha Khurma, Ruba Abu García-Arenas, Maribel Castillo, Pedro A. Hudaib, Amjad Faculty of Information Technology Zarqa University Zarqa Jordan Applied Science Private University Amman Jordan MEU Research Unit Faculty of Information Technology Middle East University Amman11831 Jordan Department of Computer Engineering Automation and Robotics University of Granada Granada Spain King Abdullah II School for Information Technology The University of Jordan Amman Jordan

Software requirements prioritization plays a crucial role in software development. It can be viewed as the process of ordering requirements by determining which requirements must be done first and which can be done later. Powerful requirements prioritization techniques are of paramount importance to finish the implementation on time and within budget. Many factors affect requirement prioritization such as stakeholder expectations, complexity, dependency, scalability, risk, and cost. Therefore, finding the proper order of requirements is a challenging process. Hence, different types of requirements prioritization techniques have been developed to support this task. In this survey, we propose a novel classification that can classify the prioritization techniques under two major classes: relative and exact prioritization techniques class, where each class is divided into two subclasses. We depend in our classification on the way the value of ranking is given to the requirement, either explicitly as a specific value in the case of the exact prioritization techniques class, or implicitly in the case of the Relative prioritization technique class. An overview of fifteen different requirements prioritization techniques are presented and organized according to the proposed classification criteria’s. Moreover, we make a comparison between methods that are related to the same subclass to analyze their strengths and weaknesses. Based on the comparison results, the properties for each proposed subclass of techniques are identified. Depending on these properties, we present some recommendations to help project managers in the process of selecting the most suitable technique to prioritize requirements based on their project characteristics (number of requirements, time, cost, and accuracy). © 2024, CC BY.

关键词： Requirements engineering

A Proposal of Speed Sensorless Control Based on IRM-ILQ Control for SPMSM Drive with Active LC Filter

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A Proposal of Speed Sensorless Control Based on IRM-ILQ Cont...

International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Ryoki Mikami Kazuki Abe Hiroshi Takami Fuminori Ishibashi Graduate School of Electrical Eng. And Computer Science Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. and Robotics Course College of Engineering Shibaura Institute of Technology Koto-ku Tokyo Japan Dept. of Electrical Eng. Faculty of Eng. Shibaura Institute of Technology Koto-ku Tokyo Japan

ISBN: (数字)9798350375589

ISBN: (纸本)9798350375596

Generally, a position detector has been used to drive the Surface Permanent Magnet Synchronous Motor (SPMSM), because the current and voltage must be controlled according to the magnetic pole position of the rotor. However, using a position detector causes problems such as more expensive and lower reliability due to position detector failure. Therefore, the speed sensor-less control, which estimates the magnetic pole position from voltage and current without using a position detector, is required. Harmonic components in the output voltage waveform of the PWM inverter used to drive the SPMSM can cause problems such as Electromagnetic Interference (EMI). Harmonic components can be suppressed by using an LC filter. In addition, IRM-ILQ control, which combines modern control theory's Inverse Linear Quadratic (ILQ) control and Inverse Reference Model (IRM), can achieve stable and robust SPMSM drive despite with LC filter. In this paper, robustness of speed sensorless control based on IRM-ILQ current control for SPMSM with active LC filter is described. In simulation, the proposed method allows stable control even when there are parameter errors.

关键词： Maximum likelihood detection Magnetic separation Electromagnetic interference Sensorless control Detectors Nonlinear filters Drives Harmonic analysis Voltage control Power harmonic filters

Evaluating Immersive Teleoperation Interfaces: Coordinating Robot Radiation Monitoring Tasks in Nuclear Facilities

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Evaluating Immersive Teleoperation Interfaces: Coordinating ...

IEEE International Conference on robotics and Automation (ICRA)

作者： Harvey Stedman Basaran Bahadir Kocer Nejra van Zalk Mirko Kovac Vijay M. Pawar Department of Computer Science Autonomous Manufacturing Laboratory University College London London UK Aerial Robotics Laboratory Imperial College London London UK Department of Aerospace Engineering University of Bristol Bristol UK Dyson School of Design Engineering Imperial College London London UK Laboratory of Sustainability Robotics at the Swiss Federal Laboratories for Materials Science and Technology Switzerland

We present a virtual reality (VR) teleoperation interface for a ground-based robot, featuring dense 3D environment reconstruction and a low latency video stream, with which operators can immersively explore remote environments. At the UK Atomic Energy Authority's (UKAEA) Remote Applications in Challenging Environments (RACE) facility, we applied the interface in a user study where trained robotics operators completed simulated nuclear monitoring and decommissioning style tasks to compare VR and traditional teleoperation interface designs. We found that operators in the VR condition took longer to complete the experiment, had reduced collisions, and rated the generated 3D map with higher importance when compared to non-VR operators. Additional physiological data suggested that VR operators had a lower objective cognitive workload during the experiment but also experienced increased physical demand. Overall the presented results show that VR interfaces may benefit work patterns in teleoperation tasks within the nuclear industry, but further work is needed to investigate how such interfaces can be integrated into real world decommissioning workflows.

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KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation

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arXiv 2024年

作者： Tao, Wei Zhou, Yucheng Wang, Yanlin Zhang, Hongyu Wang, Haofen Zhang, Wenqiang Shanghai Engineering Research Center of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China School of Software Engineering Sun Yat-sen University Guangdong Zhuhai519082 China School of Big Data and Software Engineering Chongqing University Chongqing China College of Design and Innovation Tongji University Shanghai China Engineering Research Center of AI and Robotics Ministry of Education Academy for Engineering and Technology Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University 220 Handan Road Shanghai200433 China

Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods are trained on the entire dataset without considering the fact that a portion of commit messages adhere to good practice (i.e., good-practice commits), while the rest do not. On the basis of our empirical study, we discover that training on good-practice commits significantly contributes to the commit message generation. Motivated by this finding, we propose a novel knowledge-aware denoising learning method called KADEL. Considering that good-practice commits constitute only a small proportion of the dataset, we align the remaining training samples with these good-practice commits. To achieve this, we propose a model that learns the commit knowledge by training on good-practice commits. This knowledge model enables supplementing more information for training samples that do not conform to good practice. However, since the supplementary information may contain noise or prediction errors, we propose a dynamic denoising training method. This method composes a distribution-aware confidence function and a dynamic distribution list, which enhances the effectiveness of the training process. Experimental results on the whole MCMD dataset demonstrate that our method overall achieves state-of-the-art performance compared with previous methods. © 2024, CC BY.

关键词： Sampling

Enhancing Precision Agriculture Through Human-in-the-Loop Planning and Control

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Enhancing Precision Agriculture Through Human-in-the-Loop Pl...

IEEE International Conference on Automation science and Engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

DPM-OT: A New Diffusion Probabilistic Model Based on Optimal Transport

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arXiv 2023年

作者： Li, Zezeng Li, ShengHao Wang, Zhanpeng Lei, Na Luo, Zhongxuan Gu, Xianfeng School of Software Dalian University of Technology China Beijing Key Laboratory of Light-field Imaging and Digital Geometry Capital Normal University China School of Mathematical Sciences University of the Chinese Academy of Sciences China Computer Science and Applied Mathematics State University of New York Stony Brook United States

Sampling from diffusion probabilistic models (DPMs) can be viewed as a piecewise distribution transformation, which generally requires hundreds or thousands of steps of the inverse diffusion trajectory to get a high-quality image. Recent progress in designing fast samplers for DPMs achieves a trade-off between sampling speed and sample quality by knowledge distillation or adjusting the variance schedule or the denoising equation. However, it can’t be optimal in both aspects and often suffer from mode mixture in short steps. To tackle this problem, we innovatively regard inverse diffusion as an optimal transport (OT) problem between latents at different stages and propose the DPM-OT, a unified learning framework for fast DPMs with a direct expressway represented by OT map, which can generate high-quality samples within around 10 function evaluations. By calculating the semi-discrete optimal transport map between the data latents and the white noise, we obtain an expressway from the prior distribution to the data distribution, while significantly alleviating the problem of mode mixture. In addition, we give the error bound of the proposed method, which theoretically guarantees the stability of the algorithm. Extensive experiments validate the effectiveness and advantages of DPM-OT in terms of speed and quality (FID and mode mixture), thus representing an efficient solution for generative modeling. Source codes are available at https://***/cognaclee/DPM-OT Copyright © 2023, The Authors. All rights reserved.

关键词： Diffusion