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arXiv 2025年

作者： Zhang, Dengke Tang, Quan Liu, Fagui Mei, Haiqing Chen, C.L. Philip The School of Computer Science and Engineering South China University of Technology Guangzhou510006 China The Department of New Network Pengcheng Laboratory Shenzhen518000 China The China Tobacco Guangdong Industrial Corporation Guangzhou510385 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100080 China

Semi-supervised semantic segmentation has witnessed remarkable advancements in recent years. However, existing algorithms are based on convolutional neural networks and directly applying them to Vision Transformers poses certain limitations due to conceptual disparities. To this end, we propose TokenMix, a data augmentation technique specifically designed for semi-supervised semantic segmentation with Vision Transformers. TokenMix aligns well with the global attention mechanism by mixing images at the token level, enhancing learning capability for contextual information among image patches. We further incorporate image augmentation and feature augmentation to promote the diversity of augmentation. Moreover, to enhance consistency regularization, we propose a dual-branch framework where each branch applies image and feature augmentation to the input image. We conduct extensive experiments across multiple benchmark datasets, including Pascal VOC 2012, Cityscapes, and COCO. Results suggest that the proposed method outperforms state-of-the-art algorithms with notably observed accuracy improvement, especially under limited fine annotations. Copyright © 2025, The Authors. All rights reserved.

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Multi-stage warm started optimal motion planning for over-actuated mobile platforms

arXiv

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arXiv 2022年

作者： Paz-Delgado, Gonzalo Jesús Pérez-Del-Pulgar, C.J. Azkarate, M. Kirchner, F. García-Cerezo, A. The Space Robotics Laboratory Department of Systems Engineering and Automation Universidad de Málaga Andalucia Tech Málaga29070 Spain The Automation and Robotics Section European Space Agency NoordwijkAZ 2201 Netherlands The DFKI Robotics Innovation Center Bremen Robert-Hooke-Str. 1 Bremen28359 Germany

This work presents a computationally lightweight motion planner for over-actuated platforms. For this purpose, a general state-space model for mobile platforms with several kinematic chains is defined, which considers non-linearities and constraints. The proposed motion planner is based on a sequential multi-stage approach that takes advantage of the warm start on each step. Firstly, a globally optimal and smooth 2D/3D trajectory is generated using the Fast Marching Method. This trajectory is fed as a warm start to a sequential linear quadratic regulator that is able to generate an optimal motion plan without constraints for all the platform actuators. Finally, a feasible motion plan is generated considering the constraints defined in the model. In this respect, the sequential linear quadratic regulator is employed again, taking the previously generated unconstrained motion plan as a warm start. This novel approach has been deployed into the Exomars Testing Rover of the European Space Agency. This rover is an Ackermann-capable planetary exploration testbed that is equipped with a robotic arm. Several experiments were carried out demonstrating that the proposed approach speeds up the computation time, increasing the success ratio for a martian sample retrieval mission, which can be considered as a representative use case of an over-actuated mobile platform. © 2022, CC BY.

关键词： Rovers

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LIRS-ArtBul: Design, Modelling and Construction of an Omnidirectional Chassis for a Modular Multipurpose Robotic Platform 1

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7th International Conference on Interactive Collaborative robotics, ICR 2022

作者： Apurin, Artem Abbyasov, Bulat Safarova, Liaisan Dobrokvashina, Alexandra Tsoy, Tatyana Martínez-García, Edgar A. Magid, Evgeni Laboratory of Intelligent Robotic Systems Intelligent Robotics Department Institute of Information Technology and Intelligent Systems Kazan Federal University Kremlyovskaya Str. 35 Kazan420111 Russia Institute of Engineering and Technology Department of Industrial Engineering and Manufacturing Autonomous University of Ciudad Juarez Zona Pronaf Condominio Manuel Díaz H. No. 518-B Chihuahua Cd Juárez32315 Mexico Tikhonov Moscow Institute of Electronics and Mathematics HSE University Tallinn Str 34 Moscow123458 Russia

ISBN: (数字)9783031236099

ISBN: (纸本)9783031236082

Service robotics is a promising area of commercializing robotic solutions of various kinds, from education and medical services to entertainment and advertisement. It might be useful to construct a series of different specialized service robots that have a modular construction and share the same chassis. Such approach allows to reuse encapsulated locomotion libraries instead of their development from scratch for each model of a robot and easily add or replace particular robot modules depending on a target task or an operational environment. This paper provides a tutorial on developing an omnidirectional mecanum wheeled chassis for a modular multipurpose robotic platform. We describe a chassis design, modelling in Blender, selection of components, assembly process and basic locomotion software development. We used Gazebo simulator for robot behaviour emulation due to its support of the Robot Operating System (ROS). For control Raspberry PI 4 and Arduino Mega2560 modules were employed. The chassis model behavior was validated in virtual environments of Gazebo and, after assembling, in real world locomotion scenarios. The chassis will be further employed in development of several new in-house mobile platforms, which could serve for particular purposes within the service robotics field. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mobile robots

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Accessibility-Aware Reinforcement Learning for Inclusive Robotic Navigation

Accessibility-Aware Reinforcement Learning for Inclusive Rob...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Mengsha Hu Yunhuan Wu Yibei Guo Yi Wu Chao Shi Lei Xu Rui Liu Department of Computer Science Kent State University Kent OH USA Robotics Institute Carnegie Mellon University Pittsburgh PA USA Cognitive Robotics and AI Lab (CRAI) College of Aeronautics and Engineering Kent State University Kent OH USA Informatique et Sciences du Numérique (Computer Research Laboratory) CentraleSupélec Paris-Saclay University Gif-sur-Yvette France Department of Systems Science and Industrial Engineering Binghamton University Binghamton NY USA

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Robotic navigation aids humans in essential scenarios, including airport customer boarding, commercial meeting receptions, and disaster site navigation. While individuals benefit from robotic services, these services pose accessibility challenges for people with disabilities. Robots may face limitations in mobility, vision, hearing, and cognitive reasoning, hindering disabled individuals' access to these services. As robotic services become increasingly prevalent, ensuring they are inclusive and accessible is crucial, accommodating human disabilities with adaptations such as slower movements, standing support, and hazard detection. To address this issue, this study introduces a novel Accessibility-Aware Reinforcement Learning model (ARL). ARL extracts disability-related information from human behavioral observations using a contextembedding neural network. It then adjusts robot motions to provide inclusive assistance to individuals with disabilities. To assess the effectiveness of this approach, four assisting services in navigation scenarios ('lead', 'wait', 'assist', and 'protect') and three application scenarios involving navigating elderly individuals in a museum, through traffic, and across a building patio were designed. The results validate ARL's efficacy in enabling robots to make accessibility-aware decisions, thereby enhancing their support for individuals with disabilities.

关键词： Robot motion Navigation Neural networks Reinforcement learning Feature extraction People with disabilities Robot learning Data mining Older adults Robots

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An Erasmus+ project: Interactive Course for Control Theory (ICCT) 8

An Erasmus+ project: Interactive Course for Control Theory (...

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47th Annual Conference of the IEEE industrial Electronics Society, IECON 2021

作者： Podrzaj, Primoz Finzgar, Miha Pirnar, Zan Ljubic, Sandi Lanzetta, Michele Pollini, Lorenzo Venturini, Pietro Pizag, Bertalan Urbin, Agnes Korondi, Peter Graff, Jozsef Budai, Csaba University of Ljubljana Laboratory for Mechatronics Production Systems and Automation Faculty of Mechanical Engineering Ljubljana Slovenia University of Rijeka Faculty of Engineering Department of Computer Engineering Rijeka Croatia University of Pisa Department of Industrial Engineering Department of Information Engineering Pisa Italy Budapest University of Technology and Economics Faculty of Mechanical Engineering Department of Mechatronics Optics and Mechanical Engineering Informatics Budapest Hungary

ISBN: (纸本)9781665435543

The paper presents an overview and the main results of the Erasmus+ project titled Interactive Course for Control Theory-ICCT. The project was started by four European Universities when they identified by a survey that students find Control Theory more challenging to understand compared to other subjects. The project's main goal was to develop a platform, which would offer examples from the field of Control Theory in an interactive way-ICCT. Frequently asked questions (FAQ) and test exam questions were added as well. To support the course, an accompanying textbook was prepared. At this point, the course and the accompanying textbook are available in English and the languages of the partner universities;since both of them are publicly available, we assume they will be offered in other languages in future. The benefits of implementing our interactive course are already visible in better survey results and improved grades in Control Theory-related subjects. © 2021 IEEE.

关键词： Python

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Electrolyte Effect on Photoetching of Gallium Nitride

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Nanomanufacturing and Metrology 2024年第1期7卷 61-74页

作者： Huiqiang Liang Zhenghao Wei Jiongchong Fang Yanming Li Changli Li Zhirun Xie Yun Hau Ng Guosong Zeng Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Southern University of Science and TechnologyShenzhen 518055People’s Republic of China Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen 518055People’s Republic of China School of Materials Sun Yat-Sen UniversityGuangzhou 510275People’s Republic of China School of Energy and Environment City University of Hong KongKowloon 999077Hong Kong SARPeople’s Republic of China City University of Hong Kong Shenzhen Research Institute Shenzhen Hi-Tech Industrial ParkNanshan DistrictShenzhen 518000People’s Republic of China SUSTech Energy Institute for Carbon Neutrality Southern University of Science and TechnologyShenzhen 518055People’s Republic of China

The limited material removal rate of conventional chemical mechanical polishing(CMP)significantly hinders the fabrica-tion efficiency and surface quality,thereby preventing the development of gallium nitride(GaN)-based ***,the incorporation of photoelectrochemistry in CMP has garnered increasing attention because of its potential to enhance the quality and efficiency of the GaN ***,a considerable gap still exists in the comprehensive understanding of the specific photoelectrochemical(PEC)behavior of ***,we report the influence of the electrolyte on the PEC etching of *** acids and bases were tested,with their pH being carefully *** concentrations of the cations and anions were also *** results showed that photocorrosion/photoetching was more pronounced in sulfuric acid,phosphoric acid,and nitric acid environments than in alkaline environments,but it was less pronounced in hydrochloric ***,the effects of pH and anion concentration on photoetching were investigated,and the results revealed that pho-toetching in acidic environments weakened with increasing pH levels and diminished with increasing sulfate *** underlying reasons contributing to this observation were *** findings provide ideas for improving the pho-toetching efficiency of GaN,thereby enriching the photoelectrochemical mechanical polishing(PECMP)technology of GaN.

关键词： GaN Photoelectrochemistry Photoetching pH

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Variation of sEMG with Muscle Fatigue for Lower Limb Stroke Patient During Walking

Variation of sEMG with Muscle Fatigue for Lower Limb Stroke ...

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IEEE International Conference on robotics and Biomimetics

作者： Wenze Shang Ruisen Huang Wei-Hsin Liao Xinyu Wu Fei Gao Southern University of Science and Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

sEMG signal is widely used and explored in control strategies of powered assistive human-robot interaction systems due to its non-invasive nature and ability to estimate motion intention well. However, prolonged use of the sEMG-based systems leads to muscle fatigue, contributing to unstable sEMG signals and regarding the performance of sEMG-based control strategies. In this study, three subjects, including two healthy subjects and one stroke subject, participated in our experiment, and the time domain, frequency domain, and complex features extracted from their $sEMG$ signals were utilized to evaluate muscle fatigue. The results indicate that $sEMG$ from the stroke side of the stroke subject contains more non-linear and chaotic parts, and the statistical differences between different trials are more significant, indicating that stroke has a more significant impact on the stroke side of the stroke subject. This study suggests that RMS in the stroke side of stroke subjects is less than that in others, whereas FuzzyEn in the stroke side of stroke subjects is greater than that in others, indicating that stroke leads to different motion patterns and more susceptibility to muscle fatigue.

关键词： Legged locomotion Limbs Frequency-domain analysis Biomimetics Human-robot interaction Muscles Fatigue Feature extraction Time-domain analysis Robots

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Stochastic-Robust Planning of Networked Hydrogen-Electrical Microgrids: A Study on Induced Refueling Demand

arXiv

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arXiv 2024年

作者： Sun, Xunhang Cao, Xiaoyu Zeng, Bo Zhai, Qiaozhu Başar, Tamer Guan, Xiaohong School of Automation Science and Engineering The Ministry of Education Key Laboratory for Intelligent Networks and Network Security Xi’an Jiaotong University Shaanxi Xi’an710049 China Coordinated Science Laboratory University of Illinois Urbana-Champaign UrbanaIL61801 United States Smart Integrated Energy Department Sichuan Digital Economy Industry Development Research Institute Sichuan Chengdu610037 China Department of Industrial Engineering The Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15106 United States Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing100084 China

Hydrogen-electrical microgrids are increasingly assuming an important role on the pathway toward decarbonization of energy and transportation systems. This paper studies networked hydrogen-electrical microgrids planning (NHEMP), considering a critical but often-overlooked issue, i.e., the demand-inducing effect (DIE) associated with infrastructure development decisions. Specifically, higher refueling capacities will attract more refueling demand of hydrogen-powered vehicles (HVs). To capture such interactions between investment decisions and induced refueling demand, we introduce a decision-dependent uncertainty (DDU) set and build a trilevel stochastic-robust formulation. The upper-level determines optimal investment strategies for hydrogen-electrical microgrids, the lower-level optimizes the risk-aware operation schedules across a series of stochastic scenarios, and, for each scenario, the middle-level identifies the "worst" situation of refueling demand within an individual DDU set to ensure economic feasibility. Then, an adaptive and exact decomposition algorithm, based on Parametric Column-and-Constraint Generation (PC&CG), is customized and developed to address the computational challenge and to quantitatively analyze the impact of DIE. Case studies on an IEEE exemplary system validate the effectiveness of the proposed NHEMP model and the PC&CG algorithm. It is worth highlighting that DIE can make an important contribution to the economic benefits of NHEMP, yet its significance will gradually decrease when the main bottleneck transits to other system restrictions. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

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Supporting a 'Glocal' Energy Transition: from Local Energy Communities to Global Simulation Networks

Supporting a 'Glocal' Energy Transition: from Local Energy C...

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2023 International Conference on Smart Energy systems and Technologies, SEST 2023

作者： Benedetto, G. Mazza, A. Pons, E. Bompard, E. De Paola, A. Thomas, D. Kotsakis, E. Fulli, G. Vogel, S. Monti, A. Bruno, S. Giannoccaro, G. Scala, M. La Bonfiglio, A. Invernizzi, M. Rossi, M. De Caro, F. Villacci, D. Politecnico di Torino & G-RTS Lab Department of Energy 'Galileo Ferraris' Turin Italy Joint Research Centre - European Commission Smart Grid Interoperability Laboratory Ispra Italy OPAL-RT Germany Aachen Germany Institute for Automation of Complex Power Systems Rwth Aachen University Aachen Germany Politecnico di Bari & LabZERO Department of Electrical & Information Engineering Bari Italy Università di Genova Electrical Electronics & Telecom. Eng. Naval Architecture Dep. Genoa Italy Università Del Sannio Department of Engineering Benevento Italy Università di Napoli 'Federico II' Department of Industrial Engineering Naples Italy

ISBN: (纸本)9798350397901

Managing a large share of non-dispatchable renewable energy sources requires new approaches, which have to be integrated with existing and well-established control systems currently used to guarantee power system operation. In this context, the number of energy communities is expected to increase, and hence their effective integration is fundamental. This paper aims at assessing the role and impact of energy communities on the operation of a transition power system, still having a share of active traditional power plants. Simulation models and real hardware have been included in the experiment, based on a live real-time co-simulation. The results highlight both the significant contribution that the methodology (i.e., geographically-distributed real-time co-simulation) can give in informing and driving energy transition policies and the important role that energy communities may have in supporting the transition towards completely de-carbonized power systems. © 2023 IEEE.

关键词： Renewable energy resources

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Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Models

arXiv

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arXiv 2024年

作者： Sun, Wangtao Zhang, Chenxiang Zhang, Xueyou Yu, Xuanqing Huang, Ziyang Xu, Haotian Chen, Pei He, Shizhu Zhao, Jun Liu, Kang The Laboratory of Cognition and Decision Intelligence for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China CAS Engineering Laboratory for Intelligent Industrial Vision Institute of Automation Chinese Academy of Sciences Beijing China Department of Computer Science and Engineering Texas A&M University United States Shanghai Artificial Intelligence Laboratory China Xiaohongshu Inc China AI Lab AIGility Cloud Innovation Beijing China

Although Large Language Models (LLMs) have demonstrated strong instruction-following ability, they are further supposed to be controlled and guided by inferential rules in real-world scenarios to be safe, accurate, and intelligent. This demands the possession of inferential rule-following capability of LLMs. However, no prior work has made a clear evaluation of the inferential rule-following capability of LLMs. Previous studies that try to evaluate the inferential rule-following capability of LLMs fail to distinguish the inferential rule-following scenarios from the instruction-following scenarios. Therefore, this paper first clarifies the concept of inferential rule-following and proposes a comprehensive benchmark, RuleBench, to evaluate a diversified range of inferential rule-following abilities. Our experimental results on a variety of LLMs show that they are still limited in following rules. Our analysis based on the evaluation results provides insights into the improvements for LLMs toward a better inferential rule-following intelligent agent. We further propose Inferential Rule-Following Tuning (IRFT). The experimental results show that through IRFT, LLMs can learn abstract inferential rule-following abilities from purely synthetic data and then generalize to RuleBench. The data and code can be found at: https://***/r/llm-rulefollowing-B3E3/ Copyright © 2024, The Authors. All rights reserved.

关键词： Intelligent agents

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