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arXiv 2024年

作者： Medbouhi, Aniss Aiman Marchetti, Giovanni Luca Polianskii, Vladislav Kravberg, Alexander Poklukar, Petra Varava, Anastasia Kragic, Danica Division of Robotics Perception and Learning Department of Intelligent Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

Hyperbolic machine learning is an emerging field aimed at representing data with a hierarchical structure. However, there is a lack of tools for evaluation and analysis of the resulting hyperbolic data representations. To this end, we propose Hyperbolic Delaunay Geometric Alignment (HyperDGA) – a similarity score for comparing datasets in a hyperbolic space. The core idea is counting the edges of the hyperbolic Delaunay graph connecting datapoints across the given sets. We provide an empirical investigation on synthetic and real-life biological data and demonstrate that HyperDGA outperforms the hyperbolic version of classical distances between sets. Furthermore, we showcase the potential of HyperDGA for evaluating latent representations inferred by a Hyperbolic Variational Auto-Encoder. © 2024, CC BY.

关键词： geometry

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Rearranging the Environment to Maximize Energy with a Robotic Circuit Drawing

Rearranging the Environment to Maximize Energy with a Roboti...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Tan, Xianglong Liu, Zhikang Yu, Chen Schwertfeger, Sören Rosendo, Andre Hamlyn Centre Imperial College London United Kingdom University of York Department of Computer Science United Kingdom School of Information Science and Technology ShanghaiTech University China Worcester Polytechnic Institute Robotics Engineering United States

ISBN: (纸本)9781665481090

The ability of acquiring energy form environments is greatly beneficial for robot to function in uncertain environments. In this work, we present a robot capable of drawing circuits with conductive ink while also rearranging the visual world to receive maximum energy from a power source. A range of circuit drawing tasks is designed to simulate real-world scenarios, including avoiding physical obstacles and regions that would discontinue drawn circuits. We adopt the state-of-the-art Transporter networks for pick-and-place manipulation from visual observation. We conduct experiments in both simulation and real-world settings, and our results show that, with a small number of demonstrations, the robot learns to rearrange the placement of objects (removing obstacles and bridging areas unsuitable for drawing) and to connect a power source with a minimum amount of conductive ink. As autonomous robots become more and more involved in our daily lives, our proposed approach brings a novel way for machines to keep themselves functional by rearranging their surroundings to create their own electric circuits. © 2022 IEEE.

关键词： Timing circuits

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Rethinking development and major research plans of Industrial Internet in China

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Fundamental Research 2024年第1期4卷 3-7页

作者： Chunxiao Jiang Yang Cong Jiming Chen Chenghong Wang Guozheng Wu Ruizhen Zhao Zhiheng Wang Bin Xiao Ting Chen Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Tsinghua Space Center Tsinghua UniversityBeijing 100084China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China College of Control Science and Engineering Zhejiang UniversityHangzhou 310027China Division III Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Division II Department of Information SciencesNational Natural Science Foundation of ChinaBeijing 100085China Chongqing Key Laboratory of Image Cognition School of Computer Science and TechnologyChongqing University of Posts and TelecommunicationsChongqing 400065China University of Electronic Science and Technology of China Chengdu 611731China

This paper gives a definition of the Industrial Internet and expounds on the academic connotation of the future Industrial *** this foundation,we outline the development and current status of the Industrial Internet in China and ***,we detail the avant-garde paradigms encompassed within the National Natural science Foundation of China(NSFC)’s“Future Industrial Internet Fundamental Theory and Key Technologies”research plan and its corresponding management *** research initiative endeavors to enhance interdisciplinary collaborations,aiming for a synergistic alignment of industry,academia,research,and practical *** primary focus of the research plan is on the pivotal scientific challenges inherent to the future industrial *** is poised to traverse the“first mile”,encompassing foundational research and pioneering innovations specific to the industrial internet,and seamlessly bridges to the“last mile”,ensuring the effective commercialization of scientific and technological breakthroughs into tangible industrial market *** anticipated contributions from this initiative are projected to solidify both the theoretical and practical scaffolding essential for the cultivation of a globally competitive industrial internet infrastructure in China.

关键词： Industrial Internet Academic connotation Major research plan Scientific problem Policy advice

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Self Decoupling-Reconstruction Network for Facial Expression Recognition

Self Decoupling-Reconstruction Network for Facial Expression...

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International Joint Conference on Neural Networks (IJCNN)

作者： Linhuang Wang Xin Kang Fei Ding Hai-Tao Yu Yunong Wu Kazuyuki Matsumoto Satoshi Nakagawa Fuji Ren Graduate School of Advanced Technology and Science Tokushima University Tokushima Japan Faculty of Library Information and Media Science University of Tsukuba Tsukuba Japan Dataa Robotics Chengdu China Graduate School of Information Science & Technology The University of Tokyo Tokyo Japan School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Facial Expression Recognition (FER) poses significant challenges due to various imaging conditions, including diverse head poses, lighting conditions, resolutions, and occlusions. Additionally, different personal attributes such as age, gender, and racial background further contribute to the complexity of FER. To accurately extract meaningful expression features amidst these interfering factors to enhance recognition accuracy and the model’s generalization, we propose a Self Decoupling-Reconstruction Network (SDRNet). Specifically, our approach involves two learning processes. In the first phase, the network is trained to decouple facial images with expressions into expression and neutral components. This process involves reconstructing neutral facial images and the original input, ensuring the preservation of meaningful expression components devoid of interference in the decoupling process. In the second learning phase, we employ simple convolutional neural networks (CNNs) to recognize the extracted expression components. Our method has achieved state-of-the-art results across multiple widely used datasets, providing substantial evidence of its effectiveness. Additionally, we demonstrate the robust generalization performance of our approach through cross-database evaluations.

关键词： Image resolution Image recognition Head Face recognition Neural networks Lighting Imaging

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Risk-aware Spatio-temporal Logic Planning in Gaussian Belief Spaces

Risk-aware Spatio-temporal Logic Planning in Gaussian Belief...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Matti Vahs Christian Pek Jana Tumova The authors are with the Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

In many real-world robotic scenarios, we cannot assume exact knowledge about a robot's state due to unmodeled dynamics or noisy sensors. Planning in belief space addresses this problem by tightly coupling perception and planning modules to obtain trajectories that take into account the environment's stochasticity. However, existing works are often limited to tasks such as the classic reach-avoid problem and do not provide risk awareness. We propose a risk-aware planning strategy in belief space that minimizes the risk of violating a given specification and enables a robot to actively gather information about its state. We use Risk Signal Temporal Logic (RiSTL) as a specification language in belief space to express complex spatio-temporal missions including predicates over Gaussian beliefs. We synthesize trajectories for challenging scenarios that cannot be expressed through classical reach-avoid properties and show that risk-aware objectives improve the uncertainty reduction in a robot's belief.

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Exploration of IoT Nodes Communication Using LoRaWAN in Forest Environment

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computers, Materials & Continua 2022年第6期71卷 6239-6256页

作者： Anshul Sharma Divneet Singh Kapoor Anand Nayyar Basit Qureshi Kiran Jot Singh Khushal Thakur Embedded Systems&Robotics Research Group Chandigarh UniversityMohali140413PunjabIndia Graduate School Duy Tan UniversityDa Nang550000Vietnam Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Department of Computer Science Prince Sultan UniversityRiyadh11586Saudi Arabia

The simultaneous advances in the Internet of Things(IoT),Artificial intelligence(AI)and robotics is going to revolutionize our world in the near *** recent years,LoRa(Long Range)wireless powered by LoRaWAN(LoRa Wide Area Network)protocol has attracted the attention of researchers for numerous applications in the IoT *** is a low power,unlicensed Industrial,Scientific,and Medical(ISM)bandequipped wireless technology that utilizes a wide area network protocol,i.e.,LoRaWAN,to incorporate itself into the network *** this paper,we have evaluated the LoRaWAN communication protocol for the implementation of the IoT(Internet of Things)nodes’communication in a forest *** outdoor performance of LoRa wireless in LoRaWAN,i.e.,the physical layer,has been evaluated in the forest area of Kashirampur Uttarakhand,***,the present paper aims towards analyzing the performance level of the LoRaWAN technology by observing the changes in Signal to Noise Ratio(SNR),Packet Reception Ratio(PRR)and Received Signal Strength Indicator(RSSI),with respect to the distance between IoT *** article focuses on estimating network lifetime for a specific set of LoRa configuration parameters,hardware selection and power *** the experimental results,it has been observed that transmissions can propagate to a distance of 300 m in the forest environment,while consuming approx.63%less energy for spreading factor 7 at 2 dBm,without incurring significant packet loss with PRR greater than 80%.

关键词： LoRa LoRaWAN IoT communication protocol wireless sensor networks packet reception ratio

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A Robust Model Predictive Controller for Tactile Servoing

A Robust Model Predictive Controller for Tactile Servoing

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shuai Wang Yihao Huang Wang Wei Lee Tianliang Liu Xiao Teng Yu Zheng Qiang Li Tencent Robotics X Shenzhen Guangdong China Department of Electrical & Electronic Engineering School of Engineering University of Manchester Manchester UK Department of Computer Science and Technology Shenzhen Technology University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Tactile servoing is an effective approach to enabling robots to safely interact with unknown environments. One of the core problems in tactile servoing is to robustly converge the contact features to the desired ones via a dedicated controller. This paper proposes a Data-Driven Model Predictive Controller (DDMPC) to compute the motion command given the previous interaction experience and feature deviations in tactile space. Compared with the manually designed PID-based controller, the proposed controller depends on the sound control theory and its convergence is guaranteed from a computational perspective. It is applied to the balancing control of a rolling bottle on a robotic forearm covered by a custom tactile sensor array. The real experiment demonstrates the superior robustness of the proposed approach and shows its great potential for other tactile servoing scenarios with measurement noise, which is inevitable for current tactile sensors.

关键词： Systematics System dynamics Current measurement Tactile sensors Predictive models Noise measurement Robots

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LCGen: mining in low-certainty generation for view-consistent text-to-3D 24

LCGen: mining in low-certainty generation for view-consisten...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Zeng Tao Tong Yang Junxiong Lin Xinji Mai Haoran Wang Beining Wang Enyu Zhou Yan Wang Wenqiang Zhang Shanghai Engineering Research Center of AI & Robotics Academy for Engineering & Technology Fudan University Shanghai China Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China School of Computer Science Fudan University Shanghai China Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China and Engineering Research Center of AI & Robotics Ministry of Education Academy for Engineering & Technology Fudan University Shanghai China

ISBN: (纸本)9798331314385

The Janus Problem is a common issue in SDS-based text-to-3D methods. Due to view encoding approach and 2D diffusion prior guidance, the 3D representation model tends to learn content with higher certainty from each perspective, leading to view inconsistency. In this work, we first model and analyze the problem, visualizing the specific causes of the Janus Problem, which are associated with discrete view encoding and shared priors in 2D lifting. Based on this, we further propose the LCGen method, which guides text-to-3D to obtain different priors with different certainty from various viewpoints, aiding in view-consistent generation. Experiments have proven that our LCGen method can be directly applied to different SDS-based text-to-3D methods, alleviating the Janus Problem without introducing additional information, increasing excessive training burden, or compromising the generation effect. Project page is https://***/zeng-tao/LCGen.

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RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVED MULTI-OPTIMIZATION ALGORITHM AND SUPPORT VECTOR REGRESSION 14

RESIDUAL LIFE PREDICTION OF LITHIUM BATTERY BASED ON IMPROVE...

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14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Tao, Yulong Wang, Jun Wang, Kai School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang China Key Laboratory of Intelligent Technology for Chemical Process Industry Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Robotics and Artificial Intelligence Manufacturing Innovation Institute Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781837242672

The lithium-ion battery is increasingly critical in the fields of electric vehicles and sustainable energy. Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is essential to mitigate risks and minimize potential losses. This paper introduces a novel fusion algorithm, FPSOGWO, which combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) with an enhanced Circle chaos strategy and a random adaptive weighting strategy. The FPSOGWO algorithm, integrated with Support Vector Regression (FPSOGWO-SVR), was utilized to predict the RUL of health factors in lithium batteries. Compared to other optimization algorithms, FPSOGWO exhibits superior optimization speed and value, effectively overcoming issues of local optimality. Specifically, when benchmarked against the Whale Optimization Algorithm-SVR (WOA-SVR), the R-Square values of FPSOGWO-SVR showed improvements of 15.62%, 1.28%, 5.67%, and 10.65% across four different types of batteries. Experimental results demonstrate that FPSOGWO-SVR provides more accurate RUL predictions for lithium batteries, highlighting its potential for broader application in battery health management systems. © The Institution of Engineering & technology 2024.

关键词： Support vector regression

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IP-VQA Dataset: Empowering Precision Agriculture with Autonomous Insect Pest Management through Visual Question Answering 25

IP-VQA Dataset: Empowering Precision Agriculture with Autono...

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Companion Proceedings of the ACM on Web Conference 2025

作者： Kairui Jin Xing Zi Karthick Thiyagarajan Ali Braytee Mukesh Prasad School of Computer Science University of Technology Sydney Sydney NSW Australia Smart Sensing and Robotics Laboratory (SensR Lab) Centre for Advanced Manufacturing Technology Western Sydney University Penrith NSW Australia

ISBN: (纸本)9798400713316

Precision agriculture is essential for social good, global economy and food security, yet insect pests threaten productivity through crop damage, pathogen spread, and rising pest control costs. The overuse of pesticides leads to environmental issues and pesticide resistance. Advanced technologies like Visual Question Answering (VQA) provide solutions by integrating image processing with natural language understanding, facilitating efficient pest detection and crop health monitoring. While datasets like IP102 have enhanced pest recognition, they lack necessary question-answer pairs for VQA tasks in agriculture. To address this gap, we introduce the Insect Pest Visual Question Answering (IP-VQA) dataset, designed specifically for precision agricultural applications. This dataset includes a diverse collection of high-quality images annotated with detailed question-answer pairs related to crop health, pest identification, and agricultural practices. Our thorough data collection ensures reliability and relevance. We also utilize advanced multimodal large language models to set a benchmark for the dataset. The primary contribution of the IP-VQA dataset lies in its comprehensive coverage and VQA integration within agricultural contexts. By providing rich visual and textual information, it connects VQA techniques to practical agricultural needs, supporting ongoing research and paving the way for future studies in precision agriculture.

关键词： autonomous system.

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