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Iberian robotics Conference (ROBOT)

作者： Kennedy O. S. Mota Diogo S. De Oliveira Luís Garrote Cristiano Premebida Department of Electrical and Computer Engineering University of Coimbra Institute of Systems and Robotics Coimbra Portugal

ISBN: (数字)9798350376364

ISBN: (纸本)9798350376371

This work concentrates on the problem of multisensor people detection using YOLO trained on four distinct modalities: depth and intensity LiDAR-maps, RGB, and ‘thermal’ images. RGB cameras, ubiquitous in this application domain, offer great resolution but struggle with adverse lighting conditions resulting in overexposed or underexposed images which then impact negatively on the performance of the algorithms. Thermal (long-wave infrared) cameras are more resilient against varying light conditions and provide complementary textural features, although with lower resolution when compared to RGB cameras. LiDAR sensors, while having a significantly low resolution, contribute to a physically interpretable mapping of the environment providing precise information regarding size/dimension and location of the objects. The main goal of this work is to tackle people detection using deep-models trained on single and multi-modality representations. To support the experimental part this work introduces a new multimodal dataset (called MID-3K). MID-3K allows the development of data fusion strategies by leveraging four modalities (obtained from three distinct exteroceptive sensors mounted on a mobile robot). Leveraging on a single-modality YOLO framework, we propose a multimodal representation learning approach to improve the baseline performance and to capture more relevant features across all input modalities. The evaluation of the proposed detection pipeline is conducted on the MID-3K dataset, where the reported results are grounded on state-of-the-art performance measures. The new dataset is available in a GitHub repository 1 1 MID-3K dataset: https://***/MID-3K/.

关键词： YOLO Representation learning Training Image resolution Laser radar Robot vision systems Thermal sensors Sensor fusion Cameras Software development management

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Enhancement of Two-Photon Fluorescence Microscopy Through Auxiliary Microspheres for Microscopic Observation 14

Enhancement of Two-Photon Fluorescence Microscopy Through Au...

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14th IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems, CYBER 2024

作者： Zhang, Feng Jin, Zijian Jiang, Chaodi Yuan, Shuai Yang, Yongliang Wang, Xiaoduo School of Electrical & Control Engineering Shenyang Jianzhu University Liaoning Province Shenyang110168 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Province Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798331506056

At present, it is still a great challenge to improve the observation accuracy of two-photon fluorescence microscope. A new method that using auxiliary microspheres as movable components on the sample is proposed to solve this challenge in this study, it can improve high-resolution imaging. In experiments using two-photon fluorescence microscopy, the half-width height (FWHM) of red fluorescent nanoparticles with a diameter of 20 nm was observed to be 296 nm using a primitive microscope system. In this paper by combining barium titanate microspheres with two-photon fluorescence microscopy, the accuracy of the point spread function of the nanoparticles can be improved by a factor of about 1.65, which results in a significant reduction of their half-width height measurements to 179 nm. The research is of great significance to improve the resolution of two-photon fluorescence microscope. This progress is very valuable for studying biological tissues and cell structures, it provides a new impetus for the sustainable development in the microscopic imaging field. © 2024 IEEE.

关键词： Microspheres

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A Hybrid EEG-EMG Framework for Humanoid Control using Deep Learning Transformers

A Hybrid EEG-EMG Framework for Humanoid Control using Deep L...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Olikkal, Parthan Pillai, Branesh M. Suthakorn, Jackrit Ali, Habib Vinjamuri, Ramana University of Maryland Baltimore County Vinjamuri lab Department of Computer Science and Electrical Engineering BaltimoreMD21220 United States Mahidol University Center for Biomedical and Robotics Technology Nakorm Pathom Salaya Thailand

ISBN: (纸本)9781665481090

Brain-computer interfaces (BCIs) offer promising solutions for upper limb rehabilitation. Despite advancements in deep learning, traditional models for motor rehabilitation using electroencephalography (EEG) or electromyography (EMG) to control assistive devices require enhancement. This study aims to enhance motor control capabilities by integrating EEG and EMG signals using a Transformer-based deep learning model. Ten able-bodies subjects performed center-out tasks on a low-cost upper limb rehabilitation table, capturing 2D kinematic data, EEG, and EMG signals simultaneously. The tasks varied in complexity across four levels. Preprocessed EEG and EMG signals were fused and given as input to the proposed model, which was evaluated using three performance metrics. Results showed that the EEG-EMG combined model achieved 87.27% accuracy across all the four levels. Furthermore, the model's output successfully controlled a humanoid robot to replicate similar movements. These findings highlight the efficacy of combined EEG-EMG data in improving accuracy and performance in BCI applications, advancing assistive technologies and neurorehabilitation interventions. © 2024 IEEE.

关键词： Anthropomorphic robots

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Toy Box Optics: Hiding Messages in Plain Sight

Toy Box Optics: Hiding Messages in Plain Sight

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Education and Training in Optics and Photonics (ETOP), IEEE Conference on

作者： S. Binder M. Fok Photonics and Soft Robotics Lab School of Electrical and Computer Engineering University of Georgia Athens GA

ISBN: (数字)9798331543013

ISBN: (纸本)9798331543020

Different properties of light such as polarization and its diverse wavelength spectrum, are commonly utilized throughout our daily lives. Using easy to obtain household items, we can perform activities illustrating the concept of light properties and principle of how these concepts are used in various applications. In this paper, we design and demonstrate two easy-to-follow activities to introduce how messages can be displayed or hidden using light’s properties. First, light from liquid crystal display (LCD) is used, which oscillates at a certain orientation or polarization. Messages from an LCD can be blocked from view if an observer is wearing polarized sunglasses with a polarization that is perpendicular to that of the LCD. Using an acrylic sheet, the LCD light’s polarization can be rotated, allowing the observer to see the LCD content. In our second experiment, messages written in different colors can be hidden in plain sight using a translucent putty of the same color. Putty reflects and scatters light that is of the same color. When the message and putty color matches, there is no light of the same color reflected off of the message. Making the message invisible to the viewer. Video demonstrations of both experiments can be found on the YouTube channel Play with Light. By using familiar objects, these demonstrations allow students to learn through play. Students can gain better insight into the nature of how light interacts with our surroundings to hide or reveal content. Providing greater insight into how modern technology utilizes these properties.

关键词： Training Video on demand Toy manufacturing industry Color Observers Liquid crystal displays Web sites Plastics Optical scattering Photonics

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Exploring Innovations in Autonomous robotics and Mechatronics: Application in Manufacturing and Healthcare 5

Exploring Innovations in Autonomous Robotics and Mechatronic...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Shalini, T.Grace Ganeshabu, L. Chemudugunta, Priyanka Yamsani, Nagendar Kumar, Ch.Ashok Athiraja, A. School of Computing Department of Computational Intelligence Chengalpattu Tamil Nadu Kattankulathur India Rajalakshmi Engineering College Department of Robotics and Automation Thandalam Mevalurkuppam Rajalakshmi Nagar Tamil Nadu Chennai India Karpaga Vinayaga College of Engineering and Technology Department of Robotics and Automation Tamil Nadu Chengalpattu India Sr University Department of School of Computer Science and Artificial Engineering Warangal India Malla Reddy Engineering College Department of Mechanical Engineering Main Campus Hyderabad Telangana Maisammaguda India Telangana Secunderabad India

ISBN: (纸本)9798331504403

Autonomous robotics and mechatronics have drastically changed the manufacturing and healthcare sectors by increasing productivity, precision, and flexibility. This work addresses the pressing need for new methods to advance these sectors by merging intelligent algorithms with autonomous systems. A hybrid strategy was employed, combining Deep Reinforcement Learning (DRL) and Adaptive Control Systems (ACS), to develop and optimize robotic operations. Extensive studies were conducted to assess the success of this strategy, which demonstrated a 25% reduction in operating expenses and a 30% increase in production efficiency in manufacturing settings. The method produced a precision rate of about 99% in the healthcare industry, which is significantly better than the 93% average of current systems. It also reduced patient recovery times by an estimated 20%. These results highlight the improved performance and promise of ACS with DRL combination in autonomous robotics, which may have revolutionary implications for the manufacturing and healthcare industries. The success, highlighted by economic and medical benefits, demonstrates the efficacy of our methodology and provides a strong platform for future developments in autonomous robotics and mechatronics. © 2024 IEEE.

关键词： Deep reinforcement learning

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Human-Inspired Anticipatory Motion Planning for Robotic Manipulators in Contact Tasks

Human-Inspired Anticipatory Motion Planning for Robotic Mani...

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IEEE International Conference on robotics and Biomimetics

作者： Malak Slim Naseem Daher Imad H. Elhajj Electrical and Computer Engineering Department Vision and Robotics Lab American University of Beirut Lebanon

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

In this work, we present a novel solution aimed at improving robotic manipulators' performance in contact tasks. Inspired by the human motor control system, which relies on a feedforward mechanism to anticipate and plan movements based on the physical properties of the target environment, our approach plans the robot's motion during the reaching phase, prior to contact. To validate our approach, we conducted experiments using the KUKA youBot arm in two distinct environments, represented by soft and hard materials. Results showed that the robot exhibited compliant behavior, with an average reduction of 71% in overshoot, 60% in rise-time, and 68% steady-state error of the force control response during contact.

关键词： Robot motion Motor drives computer vision Estimation Manipulators Planning Steady-state Force control Feedforward systems Robots

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Motion planning for robotics:A review for sampling-based planners

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Biomimetic Intelligence & robotics 2025年第1期5卷 15-34页

作者： Liding Zhang Kuanqi Cai Zewei Sun Zhenshan Bing Chaoqun Wang Luis Figueredo Sami Haddadin Alois Knoll School of Computation Information and Technology(CIT)Technical University of MunichMunich 85748Germany Munich Institute of Robotics and Machine Intelligence(MIRMI) Technical University of MunichMunich 80992Germany School of Control Science and Engineering Shandong UniversityJinan 250061China School of Computer Science University of NottinghamNottingham 315199United Kingdom

Recent advancements in robotics have transformed industries such as manufacturing,logistics,surgery,and planetary exploration.A key challenge is developing efficient motion planning algorithms that allow robots to navigate complex environments while avoiding collisions and optimizing metrics like path length,sweep area,execution time,and energy *** the available algorithms,sampling-based methods have gained the most traction in both research and industry due to their ability to handle complex environments,explore free space,and offer probabilistic completeness along with other formal *** their widespread application,significant challenges still *** advance future planning algorithms,it is essential to review the current state-of-the-art solutions and their *** this context,this work aims to shed light on these challenges and assess the development and applicability of sampling-based ***,we aim to provide an in-depth analysis of the design and evaluation of ten of the most popular planners across various *** findings highlight the strides made in sampling-based methods while underscoring persistent *** work offers an overview of the important ongoing research in robotic motion planning.

关键词： robotics Motion planning Sampling-based algorithms

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Finding Optimal Nash Equilibria in Multiplayer Games via Correlation Plans 22

Finding Optimal Nash Equilibria in Multiplayer Games via Cor...

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22nd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2023

作者： Zhang, Youzhi An, Bo Subrahmanian, V.S. Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science & Innovation CAS Hong Kong School of Computer Science and Engineering Nanyang Technological University Singapore Department of Computer Science Northwestern University Evanston United States

Designing efficient algorithms to compute a Nash Equilibrium (NE) in multiplayer games is still an open challenge. In this paper, we focus on computing an NE that optimizes a given objective function. Finding an optimal NE in multiplayer games can be formulated as a mixed-integer bilinear program by introducing auxiliary variables to represent bilinear terms, leading to a huge number of bilinear terms, making it hard to solve. To overcome this challenge, we propose a novel algorithm called CRM based on a novel mixed-integer bilinear program with correlation plans for some subsets of players, which uses Correlation plans with their Relations to strictly reduce the feasible solution space after the convex relaxation of bilinear terms while Minimizing the number of correlation plans to significantly reduce the number of bilinear terms. Experimental results show that our algorithm can be several orders of magnitude faster than the state-of-the-art baseline. © 2023 International Foundation for Autonomous Agents and Multiagent Systems (***). All rights reserved.

关键词： Computation theory

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Protein-Folding Inspired Programmable Control System for Robot Swarms

Protein-Folding Inspired Programmable Control System for Rob...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhang, Feng Gu, Yuping Wang, Zebin Yuan, Shuai Yang, Yongliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110106 China School of Computer Science and Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China

ISBN: (纸本)9781665481090

In swarm robotics, most of the control algorithms are inspired by the behaviors of animal swarms. The capability gap between robots and animals, however, hinders the reliability of these algorithms. Toward developing reliable algorithms of robot swarms, a promising solution is learning from the collective behaviors of low-intelligent natural swarms, such as cell collectives and molecular assemblies. Here, we proposed a programmable control system inspired by protein folding. Using our homemade RoboFold platform, we demonstrated a protein-folding inspired programmable control method for robot swarms. By programming and designing the sequence of a thread of protein-like robots, the developed system can mimic the formation of hierarchical structures in robot swarms as the three-level of protein structures. We quantitatively characterized the specific features of self-organized morphologies. The experimental results together demonstrated the feasibility of this method. To summarize, this work successfully translated the principles of protein-folding into programming methods to control the morphology of robot swarms. Considering that the protein folding problem is essentially a physicochemical problem, this system is not only beneficial for the control of swarm robots but also has the potential to develop into a tool for studying the protein folding problem. © 2024 IEEE.

关键词： Robot programming

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Underwater Exploration with Sonar of the Flooded Basement of a WW-II Submarine Bunker in the Context of the Digitization of Cultural Heritage

Underwater Exploration with Sonar of the Flooded Basement of...

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OCEANS

作者： Tim Hansen Frederike Buda Andreas Birk Robotics Computer Science and Electrical Engineering Constructor University Bremen

Underwater mapping based on the registration of data from a mechanical scanning sonar (MSS) is presented. The specific use-case is the exploration of the flooded basement of the U-Boot Bunker Valentin in the context of the digitization of this World-War-II memorial. The visibility in the basement, which is inaccessible for divers due to safety reasons, is very poor. Hence, maps are very helpful if not essential for the exploration of this environment, for which - despite its rather recent history - open questions exist. The mapping is conducted with a very robust method in form of Fourier-SOFT 2D (FS2D), which is well suited for real-time registration of the very noisy scans generated with simple motion-compensation from the MSS data. More precisely, the exploration of the bunker basement is conducted with low-cost hardware in form of a BlueROV2 vehicle, simple navigation sensors, and a Ping360 MSS. We show that reasonable maps can be generated in real-time with this equipment when using FS2D.

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