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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023

作者： Shakerimov, Aidar Sarmonov, Shamil Amirova, Aida Oralbayeva, Nurziya Zhanatkyzy, Aida Telisheva, Zhansaule Aimysheva, Arna Sandygulova, Anara Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan Graduate School of Education Nazarbayev University Astana Kazakhstan

ISBN: (纸本)9781450394222

In Kazakhstan, the ongoing Cyrillic-to-Latin alphabet shift raises challenges for early literacy development and acquisition in the Kazakh language. This paper proposes the QWriter system to help young children learn the Latin-based Kazakh alphabet and its handwriting. The system consists of a humanoid robot NAO, a tablet with a stylus, and a Reinforcement Learning (RL) agent that learns a child's mistakes and progress to maximize alphabet learning in the shortest period of time by adapting the order of practice words according to the child's mistakes. To evaluate the effectiveness of the QWriter system, we conducted a between-subject design experiment with 59 Kazakh children aged 6-8 years old and compared their learning performance with a human tutor and the CoWriting Kazakh robot system. The results did not support our assumption, we found that the proposed system received significantly higher likability scores than the baseline human tutor. © 2023 Owner/Author.

关键词： Reinforcement learning

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Target Tracking Control of Space-Manipulators on Lie Groups

Target Tracking Control of Space-Manipulators on Lie Groups

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Moghaddam, Borna Monazzah Chhabra, Robin Carleton University Autonomous Space Robotics and Mechatronics Laboratory Mechanical and Aerospace Engineering Department OttawaONKIS 5B6 Canada

ISBN: (纸本)9798350337020

We present a full-pose end-effector control approach on Lie groups for free-floating space manipulators with non-zero momentum while tracking a moving target during proximity operations. We model space-manipulators as open-chain multi-body systems with 1-degree-of-freedom joints where the configuration space of the spacecraft is isomorphic to the Special Euclidean group SE(3). We formulate the dynamics of the spacecraft-manipulator via the Lagrange-Poincare equations and the dynamics of its target via Euler-Poincare equations to avoid kinematic singularities associated with parametrization of their poses. This model reduces the phase space of the space-manipulator by exploiting its inherent independence of the spacecraft's pose. We consider the full pose of the end-effector relative to the target as the system output, which transforms the output-tracking control problem into an output-regulation problem. To avoid parametrization singularities of this output, we perform feedback linearization on the matrix Lie group SE (3) in the reduced phase space of the space-manipulator. We then propose a feedback/feedforward proportional-integral-derivative workspace controller, based on coordinate-free pose and velocity error functions defined on the matrix Lie group associated with the target's relative pose. We provide analytical proof of the almost-global stability of the presented controller when regulating the end-effector's pose relative to the target towards identity. © 2023 IEEE.

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Micro-Seismic Event Detection using statistical feature extraction and machine learning techniques 7

Micro-Seismic Event Detection using statistical feature extr...

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7th IEEE International conference for Convergence in Technology, I2CT 2022

作者： Chakraborty, Mainak Das, Manisha Aruchamy, Srinivasan Indian Institute of Engineering Science and Technology School of Mechatronics and Robotics Shibpur India CSIR- Cmeri Robotics and Automation Group Durgapur India

ISBN: (纸本)9781665421683

In this paper, we propose a novel methodology for micro-seismic event detection using multiple statistical feature extraction and machine learning techniques. The method is based on amplitude thresholding and is grounded on the idea, that each relevant seismic event crosses a particular threshold value. We have created a unique dataset of movement, hammering and no-movement using off-the-shelve geophones and 16-bit analog to digital converter. The data is sampled at 10000Hz. Each recorded dataset is of duration 2 min. The data recorded is passed through amplitude thresholding method. Multiple statistical features like root mean square, standard deviation, variance, minimum value and maximum value are extracted from the dataset in both time and frequency domain. k-fold cross validation is done to obtain validation accuracy. We have explored various machine learning algorithms and the results are discussed here. Among all classifiers, Random Forest algorithm achieves the overall highest accuracy of 92.76%. © 2022 IEEE.

关键词： Decision trees

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Investigating the Fretting of Steel Surfaces in the Presence of Hybrid Anti-Fretting Paste Containing Talc-Graphite-hBN-Molybdenum Disulfide Solid Lubricants

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Journal of Bio- and Tribo-Corrosion 2024年第4期10卷 1-11页

作者： Bhaumik, Shubrajit Krishna, Boddu Anurag Paleu, Viorel Choudhury, Nabajit Dev Department of Mechanical Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Tamil Nadu Chennai601103 India Mechanical Engineering Mechatronics & ampRobotics Department Mechanical Engineering Department "Gheorghe Asachi" Technical University of Iași 43 Prof. D. Mangeron Bld Iasi700050 Romania Department of Energy Engineering Assam Science and Technology University Assam Jalukbari Guwahati781013 India

The present work proposes a novel combination of additives dispersed in mineral oil to form a paste that exhibited significant anti-fretting properties as compared to a molybdenum-di-sulfide-containing commercial paste. The proposed paste contained 20 wt% MoS2 apart from 20 wt% talc, 15 wt%. graphite to 10 wt% hBN as additives, and 65 wt% mineral oil. The average mass of the bearing raceway tested with the proposed paste was 0.0063 ± 0.0045 g thus, exhibiting 82% less average mass loss than the bearing raceways tested with commercial paste (0.0354 ± 0.0021 g). Additionally, the machine vision system exhibited 40% fewer false brinelling areas with the proposed paste (0.9400 ± 0.108 mm2) as compared to the commercial paste (1.605 ± 0.822 mm2). Optical microscope images of the false brinelling areas further indicated debris adhesion, plastic deformation, and crack formation during the fretting phenomenon. Furthermore, the Raman spectrograph indicated the deposition of the solid lubricants on the steel surfaces during the fretting tests. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Talc

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Strain sensor on a chip for quantifying the magnitudes of tensile stress on cells

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Microsystems & Nanoengineering 2024年第3期10卷 305-315页

作者： Yuyin Zhang Yue Wang Hongze Yin Jiahao Wang Na Liu Songyi Zhong Long Li Quan Zhang Tao Yue School of Mechatronics Engineering and Automation Shanghai UniversityShanghaiChina School of Future Technology Shanghai UniversityShanghaiChina Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical EngineeringZhejiang UniversityHangzhouChina Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai UniversityShanghaiChina Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghaiChina

During cardiac development,mechanotransduction from the in vivo microenvironment modulates cardiomyocyte growth in terms of the number,area,and arrangement ***,the response of cells to different degrees of mechanical stimuli is ***-on-a-chip,as a platform for investigating mechanical stress stimuli in cellular mimicry of the in vivo microenvironment,is limited by the lack of ability to accurately quantify externally induced ***,previous technology lacks the integration of external stimuli and feedback sensors in microfluidic platforms to obtain and apply precise amounts of external ***,we designed a cell stretching platform with an in-situ *** in-situ liquid metal sensors can accurately measure the mechanical stimulation caused by the deformation of the vacuum cavity exerted on *** platform was applied to human cardiomyocytes(AC16)under cyclic strain(5%,10%,15%,20 and 25%),and we found that cyclic strain promoted cell growth induced the arrangement of cells on the membrane to gradually unify,and stabilized the cells at 15%amplitude,which was even more effective after 3 days of *** platform’s precise control and measurement of mechanical forces can be used to establish more accurate in vitro microenvironmental models for disease modeling and therapeutic research.

关键词： stress deformation arrangement

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Optimizing Base Placement of Surgical Robot: Kinematics Data-Driven Approach by Analyzing Working Pattern

arXiv

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arXiv 2024年

作者： Yoon, Jeonghyeon Park, Junhyun Park, Hyojae Lee, Hakyoon Lee, Sangwon Hwang, Minho The Department of Robotics and Mechatronics Engineering DGIST Daegu42988 Korea Republic of

In robot-assisted minimally invasive surgery (RAMIS), optimal placement of the surgical robot base is crucial for successful surgery. Improper placement can hinder performance because of manipulator limitations and inaccessible workspaces. Conventional base placement relies on the experience of trained medical staff. This study proposes a novel method for determining the optimal base pose based on the surgeon's working pattern. The proposed method analyzes recorded end-effector poses using a machine learning-based clustering technique to identify key positions and orientations preferred by the surgeon. We introduce two scoring metrics to address the joint limit and singularity issues: joint margin and manipulability scores. We then train a multi-layer perceptron regressor to predict the optimal base pose based on these scores. Evaluation in a simulated environment using the da Vinci Research Kit shows unique base pose score maps for four volunteers, highlighting the individuality of the working patterns. Results comparing with 20,000 randomly selected base poses suggest that the score obtained using the proposed method is 28.2% higher than that obtained by random base placement. These results emphasize the need for operator-specific optimization during base placement in RAMIS. Copyright © 2024, The Authors. All rights reserved.

关键词： Robotic surgery

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Resampling Strategies for Increasing Point Density in Narrow Passages for Probabilistic Roadmaps

Resampling Strategies for Increasing Point Density in Narrow...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Bartłomiej Bonar Tomasz Buratowski Department of Robotics and Mechatronics Faculty of Mechanical Engineering and Robotics AGH University of Krakow Kraków Poland

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

This paper presents multiple point-sampling strategies for stochastic approach to path planning. Their main purpose is to increase points density in narrow corridors, which are often difficult areas to navigate using non-deterministic approach for path planning. At the same time, algorithms for distributing points over the area of narrow regions and reducing their number in open space are described as well as postprocessing algorithm distancing samples from obstacles. Simulation-based tests are performed to compare achieved results and estimate calculation times.

关键词： Navigation Gaussian distribution Probabilistic logic Vectors Path planning Computational efficiency Complexity theory

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Generating Realistic Sound with Prosthetic Hand: A Reinforcement Learning Approach 46

Generating Realistic Sound with Prosthetic Hand: A Reinforce...

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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Jeong, Taemoon Yamsani, Sankalp Hong, Jooyoung Park, Kyungseo Kim, Joohyung Choi, Sungjoon Korea University Department of Artificial Intelligence Seoul Korea Republic of University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering ChampaignIL United States Department of Robotics and Mechatronics Engineering Daegu Korea Republic of

ISBN: (纸本)9798350371499

In this study, we tackle the complex task of enabling prosthetic hands to accurately reproduce sounds, a crucial aspect for distinguishing between different materials through auditory feedback. Sound identification, such as discerning a drywall tap from that on a brick wall, significantly enhances the functionality and user experience of prosthetic devices. However, achieving this level of auditory feedback in prosthetic hands poses considerable challenges. We utilize reinforcement learning (RL) techniques to train prosthetic hands in emulating human-like sound characteristics, focusing on key auditory signals like amplitude and onset timing. Our approach integrates a detailed analysis of these sound attributes to direct the prosthetic hand's movements for the sound generation that mimics natural human actions. We developed a tailored reward function incorporating amplitude, onset strength, and timing criteria to ensure the prosthetic hand's movements align closely with the intended human-like sound output. © 2024 IEEE.

关键词： Reinforcement learning

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From AI to AGI - The Evolution of Real-Time Systems with GPT Integration

From AI to AGI - The Evolution of Real-Time Systems with GPT...

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IEEE Southeastcon

作者： Aarush Kaunteya Pande Preston Brantley Muhammad Hassan Tanveer Razvan Cristian Voicu Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta Georgia

Generative artificial intelligence (AI), particularly ChatGPT, is revolutionizing various sectors, from exercise applications to accounting software, politics, and pharmaceuticals. As versatile aerial vehicles, drones have broad applications in videography, military operations, and surveying. However, their programming and optimal utilization often require extensive training. This research tackles these challenges by utilizing ChatGPT's sophisticated logic and prompt training features to enable drones to operate autonomously in various settings, ranging from everyday tasks to emergencies like search and rescue missions. Enhancing Microsoft Research's PromptCraft robotics, the project integrates innovative algorithms and GPT-4-Vision, improving command efficiency, speed, and accuracy. This integration also leverages additional sensor data feedback, allowing the drones to process user prompts with enhanced contextual understanding. Initial results show a significant improvement in command response times and accuracy, enabling the drones to interpret and execute complex voice commands in various environments. This paper presents a multimodal framework that enriches the capabilities of voice-controlled robotic systems and broadens the scope of AI applications in real-time systems, laying the groundwork for customized AI-driven systems, including robots tailored for diverse applications and the shift towards AGI.

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Humanoid robotics Powered by Vision-Based LLM Zero Shot Interactions

Humanoid Robotics Powered by Vision-Based LLM Zero Shot Inte...

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IEEE Southeastcon

作者： Gabriel David Smith Kwasi Debrah-Pinamang Razvan Cristian Voicu Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta Georgia USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Advancements in artificial intelligence (AI) have transformed robotics by enabling systems to autonomously execute complex tasks with minimal human involvement. Traditional methods, however, often depend on costly hardware, continuous monitoring, and intricate software integration, which constrain scalability and widespread implementation. This research presents an innovative approach that combines vision-based large language models (LLMs) with zero-shot prompting to autonomously program robotic systems, including a humanoid robot equipped with dual manipulators. The proposed system harnesses contextual image data to efficiently generate task-specific code, eliminating the need for iterative corrections. Training is conducted through OpenAI's Assistant feature, utilizing documents predominantly comprising images, while continuous operation is facilitated by a self-looping mechanism. Experimental results highlight the system's capability to perform manipulator tasks with notable accuracy, paving the way for scalable, adaptive, and dynamic automation. This study addresses both practical and theoretical challenges in automation, providing a cost-effective framework for next-generation robotic systems.

关键词： Training Accuracy Automation Large language models Scalability Humanoid robots Software Stereo vision Sensors Manipulator dynamics

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