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25th IEEE International Conference on Autonomous Robot systems and Competitions, ICARSC 2025

作者： Rema, Catarina Santos, Romao Piqueiro, Henrique Matos, Diogo Miguel Oliveirat, Paulo Moura Costa, Pedro Silva, Manuel F. Department of Engineering Vila Real Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science CRIIS - Centre for Robotics in Industry and Intelligent Systems Porto4200-465 Portugal Faculty of Engineering Porto4200-465 Portugal ISEP Polytechnic of Porto rua Dr. António Bernardino de Almeida Porto4249-015 Portugal JPM Industry Vale de Cambra3731-901 Portugal

ISBN: (纸本)9798331538606

Industry 4.0 is transforming manufacturing environments, with robotics being a key technology that enhances various capabilities. The flexibility of Autonomous Mobile Robots has led to the rise of multi-robot systems in industrial settings. Considering the high cost of these robots, it is essential to determine the best fit of number and type before making any major investments. Simulation and modeling are valuable decision-support tools, allowing the simulation of different setups to address robot fleet sizing issues. This paper introduces a decision-support framework that combines a fleet manager software stack with the FlexSim simulator, helping decision-makers determine the most suitable mobile robots fleet size tailored to their needs. Unlike previous approaches, the developed solution integrates the same real robot coordination software in both simulation and actual deployment, ensuring that tested scenarios accurately reflect real-world conditions. A case study was conducted to evaluate the framework, involving multiple tasks of loading and unloading materials within a warehouse. Five different scenarios with varying fleet sizes were simulated, and their performances assessed. The analysis concluded that, for the case study under consideration, a fleet of three robots was the most suitable, considering relevant key performance indicators. The results confirmed that the developed solution is an effective alternative for addressing the problem and represents a novel technology with no prior state-of-the-art equivalents. © 2025 IEEE.

关键词： Multipurpose robots

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Repairing Reed-Solomon Codes over Prime Fields via Exponential Sums

Repairing Reed-Solomon Codes over Prime Fields via Exponenti...

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IEEE International Symposium on Information Theory

作者： Roni Con Noah Shutty Itzhak Tamo Mary Wootters Blavatnik School of Computer Science Tel Aviv University Stanford Institute for Theoretical Physics Stanford University Department of Electrical Engineering-Systems Tel Aviv University Department of Computer Science and Electrical Engineering Stanford University

This paper presents several repair schemes for lowrate Reed Solomon (RS) codes over prime fields that can repair any node by downloading a constant number of bits from each surviving node. The resulting total bandwidth is higher than the bandwidth incurred during the trivial repair; however, this is still interesting in the context of leakage-resilient secret sharing. In that language, our results give attacks that show that k-out-of-n Shamir’s Secret Sharing over prime fields for small k is not leakage resilient, even if the parties only leak a constant number of bits. To the best of our knowledge, these are the first such *** another application, we provide decoding schemes for RS codes over prime fields, where the entire RS codeword is recovered by transmitting a constant number of bits from each *** results follow from a novel connection between exponential sums and repair of RS codes. In particular, we show that nontrivial bounds on certain exponential sums imply the existence of efficient nonlinear repair schemes for RS codes over prime fields.

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Reduced-Order Model-Based Gait Generation for Snake Robot Locomotion using NMPC

arXiv

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arXiv 2025年

作者： Salagame, Adarsh Sihite, Eric Ramezani, Milad Ramezani, Alireza the Department of Electrical and Computer Engineering Northeastern University BostonMA United States California Institute of Technology PasadenaCA United States with CSIRO Robotics DATA61 CSIRO Brisbane Australia

This paper presents an optimization-based motion planning methodology for snake robots operating in constrained environments. By using a reduced-order model, the proposed approach simplifies the planning process, enabling the optimizer to autonomously generate gaits while constraining the robot’s footprint within tight spaces. The method is validated through high-fidelity simulations that accurately model contact dynamics and the robot’s motion. Key locomotion strategies are identified and further demonstrated through hardware experiments, including successful navigation through narrow corridors. Copyright © 2025, The Authors. All rights reserved.

关键词： Robot programming

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Real time full-color imaging in a Meta-optical fiber endoscope

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eLight 2023年第1期3卷 147-154页

作者： Johannes E.Froch Luocheng Huang Quentin A.A.Tanguy Shane Colburn Alan Zhan Andrea Ravagli Eric J.Seibel Karl F.Bohringer Arka Majumdar Department of Physics University of WashingtonSeattleWA 98195USA Department of Electrical and Computer Engineering University of WashingtonSeattleWA 98195USA Tunoptix Fluke Hall4000 Mason Road 300WA 98195 SeattleUSA SCHOTT North America Inc.SouthbridgeMA 01550USA Department of Mechanical Engineering University of WashingtonSeattleWA 98195USA Department of Bioengineering University of WashingtonSeattleWA 98195USA Institute for Nano-Engineered Systems University of WashingtonSeattleWA 98195USA

Endoscopes are an important component for the development of minimally invasive *** size is one of the most critical aspects,because smaller and less rigid endoscopes enable higher agility,facilitate larger accessibility,and induce less stress on the surrounding *** all existing endoscopes,the size of the optics poses a major limitation in miniaturization of the imaging *** only is making small optics difficult,but their performance also degrades with ***-optics have recently emerged as a promising candidate to drastically miniaturize optics while achieving similar functionalities with significantly reduced ***,we report an inverse-designed meta-optic,which combined with a coherent fiber bundle enables a 33%reduction in the rigid tip length over traditional gradient-index(GRIN)*** use the meta-optic fiber endoscope(MOFIE)to demonstrate real-time video capture in full visible color,the spatial resolution of which is primarily limited by the fiber *** work shows the potential of meta-optics for integration and miniaturization of biomedical devices towards minimally invasive surgery.

关键词： Endoscopy Meta-optics Nano-fabrication Biomedical engineering

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Learning optimal controllers: a dynamical motion primitive approach

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IFAC-PapersOnLine 2023年第2期56卷 4776-4782页

作者： Hugo T.M. Kussaba Abdalla Swikir Fan Wu Anastasija Demerdjieva Gitta Kutyniok Sami Haddadin Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany Department of Electrical and Electronic Engineering Omar Al-Mukhtar University Libya Mathematical Institute Ludwig-Maximilians University of Munich Germany Centre for Tactile Internet with Human-in-the-Loop (CeTI) Germany

Real-time computation of optimal control is a challenging problem and, to solve this difficulty, many frameworks proposed to use learning techniques to learn (possibly sub-optimal) controllers and enable their usage in an online fashion. Among these techniques, the optimal motion framework is a simple, yet powerful technique, that obtained success in many complex real-world applications. The main idea of this approach is to take advantage of dynamic motion primitives, a widely used tool in robotics to learn trajectories from demonstrations. While usually these demonstrations come from humans, the optimal motion framework is based on demonstrations coming from optimal solutions, such as the ones obtained by numeric solvers. As usual in many learning techniques, a drawback of this approach is that it is hard to estimate the suboptimality of learned solutions, since finding easily computable and non-trivial upper bounds to the error between an optimal solution and a learned solution is, in general, unfeasible. However, we show in this paper that it is possible to estimate this error for a broad class of problems. Furthermore, we apply this estimation technique to achieve a novel and more efficient sampling scheme to be used within the optimal motion framework, enabling the usage of this framework in some scenarios where the computational resources are limited.

关键词： Real-time optimal control Learning from control Autonomous robotic systems

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Vision-Guided Loco-Manipulation with a Snake Robot

arXiv

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arXiv 2025年

作者： Salagame, Adarsh Potluri, Sasank Vaidyanathan, Keshav Bharadwaj Gangaraju, Kruthika Sihite, Eric Ramezani, Milad Ramezani, Alireza Department of Electrical and Computer Engineering Northeastern University BostonMA United States California Institute of Technology PasadenaCA United States CSIRO Robotics DATA61 CSIRO Brisbane Australia

This paper presents the development and integration of a vision-guided loco-manipulation pipeline for Northeastern University’s snake robot, COBRA. The system leverages a YOLOv8-based object detection model and depth data from an onboard stereo camera to estimate the 6-DOF pose of target objects in real time. We introduce a framework for autonomous detection and control, enabling closed-loop loco-manipulation for transporting objects to specified goal locations. Additionally, we demonstrate open-loop experiments in which COBRA successfully performs real-time object detection and loco-manipulation tasks. Copyright © 2025, The Authors. All rights reserved.

关键词： Object detection

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Preprocessing Taste Data for Deep Neural Networks

Preprocessing Taste Data for Deep Neural Networks

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Hyunjong Lee Han Hee Jung Jeongho Kwak Junwoo Yea Jihwan P. Choi Kyung-In Jang Department of Electrical Engineering and Computer Science Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu Republic of Korea Department of Robotics and Mechatronics Engineering DGIST Daegu Republic of Korea Department of Electrical Engineering and Computer Science DGIST Daegu Republic of Korea Department of Aerospace Engineering Korea Advance Institute of Science and Technology (KAIST) Dajeon Republic of Korea

Analyzing wine using taste data is a promising field due to the explosive expansion of online commerce. However, because of the wide variety of wine types with different flavors and aromas, it is difficult for consumers to choose the wine that suits their taste, and also difficult for sellers to recommend appropriate wines to consumers. Therefore, it is necessary to numerically analyze and classify wine, and a deep learning algorithm which mimics the human brain is appropriate for analyzing the wine data [1]. In this paper, we introduce several studies of wine classification using deep learning architectures and propose preprocessing methods for applying the taste data of wine to deep learning networks.

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AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognition

arXiv

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arXiv 2021年

作者： Barros, Tiago Garrote, Luís Pereira, Ricardo Premebida, Cristiano Nunes, Urbano J. University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Portugal

LiDAR-based place recognition is one of the key components of SLAM and global localization in autonomous vehicles and robotics applications. With the success of DL approaches in learning useful information from 3D LiDARs, place recognition has also benefited from this modality, which has led to higher re-localization and loop-closure detection performance, particularly, in environments with significant changing conditions. Despite the progress in this field, the extraction of proper and efficient descriptors from 3D LiDAR data that are invariant to changing conditions and orientation is still an unsolved challenge. To address this problem, this work proposes a novel 3D LiDAR-based deep learning network (named AttDLNet) that uses a range-based proxy representation for point clouds and an attention network with stacked attention layers to selectively focus on long-range context and inter-feature relationships. The proposed network is trained and validated on the KITTI dataset and an ablation study is presented to assess the novel attention network. Results show that adding attention to the network improves performance, leading to efficient loop closures, and outperforming an established 3D LiDAR-based place recognition approach. From the ablation study, results indicate that the middle encoder layers have the highest mean performance, while deeper layers are more robust to orientation change. The code is publicly available at:https://***/Cybonic/AttDLNet. © 2021, CC BY.

关键词： Ablation

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Biodegradable Gliding Paper Flyers Fabricated Through Inkjet Printing

Biodegradable Gliding Paper Flyers Fabricated Through Inkjet...

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

作者： Luca Girardi Rui Wu Yuki Fukatsu Hiroki Shigemune Stefano Mintchev Department of Environmental Systems Science Environmental Robotics Laboratory ETH Zurich Zurich Switzerland Swiss Federal Institute for Forest Snow and Landscape Research (WSL) Birmensdorf Switzerland Department of Electrical Engineering Shibaura Institute of Technology Tokyo Japan

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Seed-inspired minimalist microflyers are showing potential as dispersal platforms for sensor networks and seeds. Their function relies on the sheer number of low-cost flyers, inevitably raising concerns about the post-operation environmental impact. We propose a biodegradable paper glider platform fabricated through origami inkjet printing. This method can fold origami along printing patterns on different paper varieties. We created a printing pattern that allows 2D paper sheets to self-fold into a 3D flying wing glider with designable wing geometry and center of gravity (CG). The design allows stable and repeatable gliding behavior, proven in our gliding tests. It successfully achieves the dispersal of multiple gliders from a hovering drone, covering an average horizontal distance larger than the release height. We also tested the biodegradation of different paper types compatible with the printing method, showing near-complete degradation after 15 weeks in moist soil. Our study presents a novel, potentially scalable approach for fabricating environmentally friendly microflyers, offering new avenues for remote environmental sensing and automated forest restoration programs.

关键词： Geometry Atmospheric modeling Forestry Aerodynamics Three-dimensional printing Stability analysis Ink jet printing Seeds (agriculture) Thermal stability Paints

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Causality from Bottom to Top: A Survey

arXiv

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arXiv 2024年

作者： Weinberg, Abraham Itzhak Premebida, Cristiano Faria, Diego Resende AI-WEINBERG AI Experts Tel Aviv Israel University of Coimbra Dept of Electrical and Computer Engineering Institute of Systems and Robotics Coimbra Portugal School of Physics Engineering and Computer Science University of Hertfordshire Hertfordshire HatfieldAL10 9AB United Kingdom

Causality has become a fundamental approach for explaining the relationships between events, phenomena, and outcomes in various fields of study. It has invaded various fields and applications, such as medicine, healthcare, economics, finance, fraud detection, cybersecurity, education, public policy, recommender systems, anomaly detection, robotics, control, sociology, marketing, and advertising. In this paper, we survey its development over the past five decades, shedding light on the differences between causality and other approaches, as well as the preconditions for using it. Furthermore, the paper illustrates how causality interacts with new approaches such as Artificial Intelligence (AI), Generative AI (GAI), Machine and Deep Learning, Reinforcement Learning (RL), and Fuzzy Logic. We study the impact of causality on various fields, its contribution, and its interaction with state-of-the-art approaches. Additionally, the paper exemplifies the trustworthiness and explainability of causality models. We offer several ways to evaluate causality models and discuss future directions. © 2024, CC BY-SA.

关键词： Fuzzy logic

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