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Brazilian Symposium on Computing System Engineering (SBESC)

作者： Diogo Martins Sara Aldhaheri Pavel Kopanev Èric Pairet Paola Ardón Alirio Sá Autonomous Robotics Research Center (ARRC) Technology Innovation Institute (TII) Abu Dhabi United Arab Emirates Mechatronics Graduate Program (PPGM) Federal University of Bahia (UFBA) Salvador Brazil

Achieving full autonomy in robotic manipulation tasks in unstructured environments remains challenging despite technological advancements. This paper introduces LOLA, a user-centric framework designed for seamless task creation across various robotic manipulators. A comparative user study with 20 participants revealed that LOLA closely matched user’s expectations highlighting its potential for broader application in robotic manipulation.

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Task Planning and Motion Control with Temporal Logic Specifications

Task Planning and Motion Control with Temporal Logic Specifi...

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

作者： Marcos S. Pereira Luciano C. A. Pimenta Bruno V. Adorno Graduate Program in Electrical Engineering Department of Electronic Engineering Universidade Federal de Minas Gerais Belo Horizonte MG Brazil Manchester Centre for Robotics and AI The University of Manchester Manchester UK

This paper proposes a task planning and motion control framework that generates task plans for a linear temporal logic specification (LTL), which are then executed using a task-space constrained motion controller and a local task planner that overcomes local minima. We propose a new encoding for task specifications, directly in the task-space, as constraints of a mixed-integer linear program that can be used with off-the-shelf LTL linear encoding. We apply our framework to plan and execute trajectories for a free-flying robot and show that the task plan is accomplished without collisions, even in the presence of unexpected moving obstacles that are not considered in the planning phase, while control signal constraints are satisfied. To evaluate the local minima avoidance, we compare the local task planner with a sampling-based motion planner, and the results show a smoother trajectory with a faster execution and less total planning time when using our framework. Last, our framework scaled well with a longer LTL specification, as opposed to automata-based frameworks that usually suffer with the curse of the dimensionality.

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A Machine Learning-Based Routing Technique for Off-chain Transactions in Payment Channel Networks 5

A Machine Learning-Based Routing Technique for Off-chain Tra...

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5th IEEE International Conference on Smart Internet of Things, SmartIoT 2021

作者： Kadry, Heba Gadallah, Yasser Robotics Control and Smart Systems Program American University in Cairo New Cairo11835 Egypt Department of Electronics and Communications Engineering American University in Cairo New Cairo11835 Egypt

ISBN: (纸本)9781665445115

Blockchain is a foundational technology that has the potential to create new prospects for our economic and social systems. However, the lack of scalability limits the capability to deliver a target throughput and latency compared to the traditional financial systems. Layer-two is a collective term for solutions designed to enhance scalability by handling transactions off the main chain. For example, bidirectional payment channels allow the execution of fast transactions between two parties, thus forming the so-called payment channel networks (PCNs). Therefore, efficient routing protocols are needed to find a payment path from the sender to the receiver, with the lowest transaction fees. These protocols have to consider, among other factors, the unexpected online/offline behavior of the constituent payment nodes and the payment channel imbalance. This study proposes a novel machine learning-based technique for off-chain transaction routing. It is a fully distributed approach to be used within PCNs. For this purpose, the effect of the offline nodes and channel imbalance on the payment channels network are modeled. The simulation results demonstrate that the proposed technique strikes a good balance when considering the success ratio, transaction fees, routing efficiency, transaction overhead, and transaction maintenance overhead compared to other techniques that have previously been proposed for the same purpose. © 2021 IEEE.

关键词： Scalability

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On the Minimal Recognizable Image Patch

On the Minimal Recognizable Image Patch

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International Conference on Pattern Recognition

作者： Mark Fonaryov Michael Lindenbaum Autonomous Systems and Robotics Program Technion Haifa Israel Haifa Israel

In contrast to human vision, common recognition algorithms often fail on partially occluded images. We propose characterizing, empirically, the algorithmic limits by finding a minimal recognizable patch (MRP) that is by itself sufficient to recognize the image. A specialized deep network allows us to find the most informative patches of a given size, and serves as an experimental tool. A human vision study recently characterized related (but different) minimally recognizable configurations (MIRCs) [1], for which we specify computational analogues (denoted cMIRCs). The drop in human decision accuracy associated with size reduction of these MIRCs is substantial and sharp. Interestingly, such sharp reductions were also found for the computational versions we specified.

关键词： Image recognition Tools Character recognition Task analysis Materials requirements planning

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Development of Detection Kidney Function Stand Alone System and Design based on Oral Ammonia Levels

Development of Detection Kidney Function Stand Alone System ...

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International Conference of Computer and Informatics Engineering (IC2IE)

作者： William Natasha Angeline Hansen Yosica Mariana Elioenai Sitepu Winda Astuti Melinda Siswanto Automotive and Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Product Design Program Industrial Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia Biotechnology Engineering Department Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331505530

ISBN: (纸本)9798331505547

The development of detection kidney function system at the first prototype have problem with the dependence on the internet, which make not practical in the development of the system and the initial design was not ergonomic. In this work the development of the second step is done with the improvement of accuracy compared with other methods. In this work the new design of the embedded system is also applied and in term of algorithm, the system applied for woman patient. Three different types of machine learning techniques, namely K-nearest neighbors (KNN), Decision Tree and Random Forest are applied and compared. The AI-based kidney failure severity identification system with KNN algorithm had an average accuracy of 90% and 91% for training and testing accuracy, respectively. The design of the embedded system also renews with stylist, simple and practical.

关键词： Training Accuracy Machine learning algorithms Embedded systems Nearest neighbor methods Vectors Decision trees Kidney Random forests Testing

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High-Curvature Consecutive Tip Steering of a Soft Growing Robot for Improved Target Reachability

High-Curvature Consecutive Tip Steering of a Soft Growing Ro...

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

作者： Dong-Geol Lee Nam Gyun Kim Jee-Hwan Ryu Robotics Program Korea Advanced Institute of Science and Tech-nology (KAIST) Daejeon Republic of Korea Department of Civil and Environmental Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea

Over the years, soft growing robots that allow the feeding of new materials at their tips have attracted considerable attention owing to their unique locomotion characteristics. However, accessing targets over highly curved passages by steering compliant continuum bodies remains challenging. To this end, this study proposes a new tip steering mechanism that imparts soft growing robots with consecutive high-curvature steering ability. We place a hyper-redundant rolling contact joint and twisted string actuator (TSA) at the tip of a soft growing robot to provide high-curvature continuous steering with a smaller scale factor, allowing consecutive turns. The proposed small form factor continuous curvature tip steering mechanism allows the steering mechanism to stay at the tip during steering, improving accessibility by enabling consecutive turns. The improved accessibility of the proposed mechanism is demonstrated based on better confined space reachability compared with that of conventional whole-body steering soft growing robots, along with a consecutive high-curvature pipe navigation demonstration.

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Mechanical Response of Tungsten g-TPMS Lattice Structures

SSRN

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SSRN 2024年

作者： Islam, Zahabul Ahmed, Tanvir Mayyas, Mohammad Abouheaf, Mohammed Mechanical and Manufacturing Engineering Program School of Engineering Bowling Green State University Bowling GreenOH43403 United States Robotics Engineering School of Engineering Bowling Green State University Bowling GreenOH43403 United States

The present study explores the mechanical behavior of tungsten gyroid Triply Periodic Minimal Surface (g-TPMS) lattice structures through atomistic simulations, focusing on models with varying lattice thickness or simply volume fractions. It examines the isotropic nature of these structures under both tensile and compressive loads. The research demonstrates that strength and ductility in g-TPMS can be adjusted through design, showcasing unique behaviors not found in bulk materials. A relationship between elastic modulus and volume fraction is established, providing coefficients for multi-scale modeling and simulation. Additionally, the study investigates the temperature-dependent mechanical response and the effects of helium embrittlement on tungsten g-TPMS and bulk tungsten, emphasizing the need for tailored materials in advanced applications like nuclear fusion reactors. © 2024, The Authors. All rights reserved.

关键词： Volume fraction

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Active Telepresence Assistance for Supervisory Control: A User Study with a Multi-Camera Tele-Nursing Robot

Active Telepresence Assistance for Supervisory Control: A Us...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Alexandra Valiton Hannah Baez Naomi Harrison Justine Roy Zhi Li Robotics Engineering Program Worcester Polytechnic Institute Worcester MA USA

Supervisory control of a humanoid robot in a manipulation task requires coordination of remote perception with robot action, which becomes more demanding with multiple moving cameras available for task supervision. We explore the use of autonomous camera control and selection to reduce operator workload and improve task performance in a supervisory control task. We design a novel approach to autonomous camera selection and control, and evaluate the approach in a user study which revealed that autonomous camera control does improve task performance and operator experience, but autonomous camera selection requires further investigation to benefit the operator’s confidence and maintain trust in the robot autonomy.

关键词： Telepresence Automation Robot kinematics Conferences Robot vision systems Humanoid robots Supervisory control

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Data Alignment Design for Robotic programming by Demonstration Based on IMU and Optical Tracker

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IEEE Transactions on Instrumentation and Measurement 2023年 72卷 1页

作者： Song, Kai-Tai Li, Bing-Yi Ou, Szu-Chen National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering College of Electrical and Computer Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Graduate Degree Program of Robotics Hsinchu300093 Taiwan

This study proposes a data alignment design for sensor fusion of an optical target (OT) and an inertial measurement unit (IMU) to track the trajectory of a handheld tool for robot programming by demonstration (PbD). A novel method is proposed for coordinate and temporal alignment between the OT and the IMU sensor to increase tracking accuracy. The IMU measurements are aligned with the corresponding angular velocities and accelerations derived from the OT to calibrate the IMU-OT relationship. Global and local optimizations are combined to reduce the computation time for the temporal alignment and coordinate calibration. Experimental results show that the proposed method provides improved calibration results with shorter calculation time compared with the two existing methods. The sensor fusion experiments verify the accuracy of trajectory tracking of 1.3 mm using the calibration result, an improvement from 1.4 mm of the data alignment using ruler measurement. Integrated PbD experiments using a 6-DOF manipulator were carried out to evaluate the proposed method. The manipulator imitated the hand motion of a bottle transfer task with a trajectory error of 0.66 mm. Practical robotic experiments demonstrate that the method is suitable for robot programming applications. © 1963-2012 IEEE.

关键词： Calibration

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Material informatics-driven insights into brain cancer nanocarriers: A bibliometric comparison of PLGA vs. liposomes

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OpenNano 2025年 21卷

作者： Makalew, Brilly Andro Abrori, Syauqi Abdurrahman Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta 11480 Indonesia

This study explores a comparative analysis of PLGA nanoparticles and liposomes as potential carriers for brain cancer drug delivery, with a special focus on how material informatics enhances their design, biocompatibility, and drug release profiles to improve treatment efficacy and contribute to sustainable health outcomes. The investigation employed a bibliometric analysis using Scopus and VOSviewer to uncover the role of material informatics in optimizing these nanocarriers. The analysis revealed that material informatics, particularly through the application of machine learning and molecular dynamics simulations, significantly optimizes the performance of both PLGA nanoparticles and liposomes. The results highlighted distinct strengths of each nanocarrier: PLGA nanoparticles excel in biodegradability, while liposomes offer superior drug encapsulation capabilities. However, material informatics techniques bridged these enhancing drug release kinetics, stability, and biocompatibility. These improvements are crucial for effective delivery across the blood-brain barrier, a major challenge in brain cancer treatment. The integration of computational modelling, machine learning, and high-throughput screening enabled by material informatics is shown to be a key factor in advancing the design and optimization of these nanocarriers. By leveraging these tools, researchers can develop more personalized and efficient drug delivery systems tailored to address the specific challenges of glioblastoma therapy, ultimately contributing to sustainable health outcomes © 2024 The Author(s)

关键词： Bibliometric analysis Brain cancer Drug delivery Liposomes Material informatics Nanocarriers PLGA nanoparticles VOSviewer

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