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IEEE International Conference on robotics and Biomimetics

作者： Xi Wu Chenzui Li Kehan Zou Ning Xi Fei Chen Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Hong Kong SAR China Department of Industrial and Manufacturing System Engineering The University of Hong Kong Hong Kong SAR China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Musculoskeletal models are pivotal in the domains of rehabilitation and resistance training to analyze muscle conditions. However, individual variability in musculoskeletal parameters and the immeasurability of some internal biomechanical variables pose significant obstacles to accurate personalized modelling. Furthermore, muscle activation estimation can be challenging due to the inherent redundancy of the musculoskeletal system, where multiple muscles drive a single joint. This study develops a whole-body musculoskeletal model for strength and conditioning training and calibrates relevant muscle parameters with an electromyography-based optimization method. By utilizing the personalized musculoskeletal model, muscle activation can be subsequently estimated to analyze the performance of exercises. Bench press and deadlift are chosen for experimental verification to affirm the efficacy of this approach.

关键词： Training Presses Analytical models Biological system modeling Estimation Optimization methods Muscles Data models Robots Load modeling

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Opto2P-FCM: A MEMS Based Miniature Two-Photon Microscope with Patterned Optogenetic Stimulation

Opto2P-FCM: A MEMS Based Miniature Two-Photon Microscope wit...

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Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics

作者： Futia, Gregory L. Zohrabi, Mo McCullough, Connor Teel, Alec de Souza, Fabio Simoes Oroke, Ryan Bright, Victor M. Restrepo, Diego Gopinath, Juliet T. Gibson, Emily A. Department of Bioengineering University of Colorado Anschutz Medical Campus AuroraCO80045 United States Department of Cell and Developmental Biology University of Colorado Anschutz Medical Campus AuroraCO80045 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Department of Mechanical Engineering University of Colorado BoulderCO80309 United States Department of Physics University of Colorado BoulderCO80309 United States Materials Science and Engineering Program University of Colorado BoulderCO80309 United States

Miniaturized microscopes for monitoring neural activity are an indispensable tool for neuroscience research. We present a novel MEMS based miniature microscope with patterned optogenetic stimulation capabilities enabl... 详细信息

ISBN: (纸本)9781957171340

关键词： Microscopes

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A Comprehensive Study on Different Optimizations of Pure Reference Counting Garbage Collectors

A Comprehensive Study on Different Optimizations of Pure Ref...

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Computational Intelligence, Networks and Security (ICCINS), International Conference on

作者： Faria Tabassum Md. Rahatul Islam Md Shoaib Ur Rahman Jimmy Majumder Department of CSE Bangladesh University of Engineering and Technology Dhaka Bangladesh Department of Human Intelligence Systems Engineering Kyushu Institute of Technology Japan Department of Mechanical Engineering Chittagong National Engineering College Bangladesh Bangladesh Advance Robotics Research Center Bangladesh

With the gradual increase of program complexity for utilities and various appliances, memory management has always been a challenge for computer scientists. Garbage collection is a very effective memory management system that comprises techniques that aim to claim unused objects which in turn returns reusable memory space for further use. Among the array of garbage collection techniques, pure reference counting (RC) is very popular that actively tracks down any unused object reference by means of keeping reference counts. It offers better reliability compared with other passive techniques. However this process cannot track cyclic garbage references. In order to solve this cycle detection issue along with other various improvements available for other techniques different methods have been proposed and developed. This paper offers an extensive examination of diverse optimization approaches designed to improve the effectiveness of garbage collectors based on Pure Reference Counting. Some of these optimizations look for loaning concepts from tracing to improve tracking down performance while others add up cycle detection from various existing techniques to gain the pros of both techniques or others simply emphasize memory allocation for reducing time complexity overhead. Our findings provide insights for researchers seeking to leverage Pure RC as a memory management solution, shedding light on the advantages and limitations of different optimization techniques. This study contributes to the ongoing discourse on memory management, offering a perspective on the specifics of Pure RC-based garbage collectors and their potential for optimization.

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Considerations on Interaction with Manipulator in Virtual Reality Teleoperation Interface for Rescue Robots*

Considerations on Interaction with Manipulator in Virtual Re...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Kotaro Kanazawa Noritaka Sato Yoshifumi Morita Department of Engineering Electrical and Mechanical Engineering Program Nagoya Institute of Technology Gokiso-cho Showa-ku Nagoya Aichi Japan

In recent years, commercially available head-mounted display and virtual reality (VR) controllers have made it possible to implement user interfaces that facilitate situational awareness and reduce operator workload. This study focuses on operator interaction and workload in a VR teleoperation interface for rescue robots. Three interaction methods are implemented in this interface, which differ in the timing between the operation in VR space and the movement of the robot. The operating characteristics of these three interaction methods and a conventionally used gamepad are compared through a manipulator teleoperation task with nine participants.

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Control Contraction Metrics on Submanifolds

Control Contraction Metrics on Submanifolds

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IEEE Conference on Decision and Control

作者： Dongjun Wu Bowen Yi Ian R. Manchester Department of Automatic Control Lund University Box 118 Lund Sweden Department of Electrical Engineering & GERAD Polytechnique Montreal QC Canada Australian Centre for Robotics and School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Australia

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we extend the control contraction metrics (CCM) approach, which was originally proposed for the universal tracking control of nonlinear systems, to those that evolves on submanifolds. We demonstrate that the search for CCM on submanifolds can be reformulated as convex conditions. In particular, since Lie groups can be viewed as submanifolds in Euclidean space, the results are directly applicable to this setting.

关键词： Measurement Lie groups Aerospace electronics Control systems Nonlinear systems

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Analyzing the Design of Windows Cleaning Robots 3

Analyzing the Design of Windows Cleaning Robots

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3rd International Conference on Big Data, Artificial Intelligence and Internet of Things engineering, ICBAIE 2022

作者： Zhang, Ao Yao, Yefan Hu, Yufan Beijing National Day School International Department Beijing China Xi'an Jiaotong-liverpool University Department of Mechatronics and Robotics Suzhou China University of Electronic Science and Technology of China Department of Mechanical and Electrical Engineering Chengdu China

ISBN: (数字)9781665451604

ISBN: (纸本)9781665451604

It is imperative to maintain a clean living and working environment. As a result of the development of the construction industry, high-rise buildings are now ubiquitous. Traditional methods of cleaning are insufficient to maintain these buildings. Considering tall buildings can be more than 100 meters above ground level, airflow speeds are greater, and protection devices are essential. Additionally, manual cleaning is slower, and accidents are more likely. Consequently, the use of automatic cleaning robots is crucial to replacing manual cleaning. Further, automatic cleaning robots have the stability and accuracy that manual cleaning does not possess. Robots are more efficient at cleaning than humans. Three different types of cleaning robot mechanisms are discussed, including adsorption mechanisms, motion mechanisms, and cleaning mechanisms, and their application areas and advantages and disadvantages are compared. In the next section, we summarize the results of comparing the various types of mechanical engineering used in the adsorption device, the motion mechanism, and the cleaning device. The evaluation concludes with an assessment of the shortcomings and recommendations for future research. A number of types of automatic window cleaning robots are presented to the reader as references. © 2022 IEEE.

关键词： Cleaning

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Evaluation of Needle Manipulation Controller Subject to Uncertainty of Tip Pose Feedback: a Simulation Study

Evaluation of Needle Manipulation Controller Subject to Unce...

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International Symposium on Medical robotics (ISMR)

作者： Junling Mei Chang Chang Yanzhou Wang Simon Leonard Iulian Iordachita Laboratory of Computational Sensing and Robotics Johns Hopkins University Baltimore MD USA Department of Mechanical Engineering Laboratory of Computational Sensing and Robotics Johns Hopkins University Baltimore MD USA Department of Computer Science Laboratory of Computational Sensing and Robotics Johns Hopkins University Baltimore MD USA

ISBN: (数字)9798331599003

ISBN: (纸本)9798331599010

In this paper, we evaluate the performance of our controller for flexible needle manipulation for percutaneous interventions in a finite element (FE) simulator. We investigate the use of electromagnetic (EM) tracking as needle tip pose feedback, and how artificial sensor noises can affect tracking performance of the controller. In our simulated study, the control system shows high targeting accuracy and robustness with an overall tip position error of 0.49 mm. The addition of needle tip orientation feedback further improves the targeting accuracy for deeper targets, with average error of 0.81 mm when only using position feedback, and 0.55 mm when using additional orientation feedback.

关键词： Target tracking Accuracy Uncertainty Medical robotics Noise Needles Robot sensing systems Robustness Finite element analysis Electromagnetics

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Comparing Z3 and A3 PKM Heads: Which Is Superior and Why?

arXiv

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arXiv 2024年

作者： Nigatu, Hassen Guodong, Lu Dong, Huixu Grasp Lab of the Mechanical Engineering Department Zhejiang University Hangzhou310058 China The Mechanical Engineering Department Zhejiang University Hangzhou310058 China Robotics Research Center of Yuyao Yuyao Technology Innovation Center No. 479 Yuyao Ningbo City Hangzhou315400 China

This study presents a comparison between the Sprint Z3 and A3 head parallel kinematics machines, distinguished by their joint sequence. The analysis focuses on performance attributes critical for precision machining—specifically, parasitic motion, workspace capability, stiffness performance over the independent and parasitic spaces, and condition number distribution. Although these machines are extensively utilized in precision machining for the aerospace and automotive industries, a definitive superior choice has not been identified for machining large components. Moreover, the distribution of stiffness across the configuration of parasitic space has not previously been addressed for either mechanism. This research reveals that despite identical parameters used and exhibiting similar parasitic motions, the Sprint Z3 demonstrates superior stiffness, workspace volume, and condition number distribution. This performance advantage is attributed to variations in joint and link sequence, which enhance deflection resilience—crucial for manufacturing large-scale components. This also results in a higher condition number and a larger workspace. The result highlights the importance of design architecture in the efficacy of parallel kinematics machines and suggest that seemingly minor differences can have significant impacts. © 2024, CC BY.

关键词： Stiffness

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Development and performance assessment of a new opensource Bayesian inference R platform for building energy model calibration

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Discover mechanical engineering 2023年第1期2卷 1-25页

作者： Hou, Danlin Zhan, Dongxue Wang, Liangzhu Hassan, Ibrahim Galal Sezer, Nurettin Centre for Zero Energy Building Studies Department of Building Civil and Environmental Engineering Concordia University 1455 de Maisonneuve Blvd. West Montreal H3G 1M8 QC Canada Mechanical Engineering Program Texas A & amp M University at Qatar P.O. Box 23874 Engineering Building Education City Al Rayyan Doha Qatar

Many factors contribute to the inherent uncertainty of energy consumption modeling in buildings. It is essential to perform a calibration and sensitivity analysis in order to manage these uncertainties. Despite the availability of several calibration methods, they are often deterministic and lack quantified uncertainties. Moreover, the selection of parameters in building energy modeling for calibration depends on the user’s experience. Therefore, a more rigorous selection process is required. This study developed a new automated Bayesian Inference calibration platform running as an R package. A sensitivity analysis module and a Bayesian inference module determine the calibration parameters and uncertainties, respectively. The Meta-model module is developed to replace the building energy model for the Markov Chain Monte Carlo process to save computing time. The proposed platform is successfully demonstrated on a synthetic high-rise office building and a real high-rise residential building in a hot and arid climate. The relationship between the number of calibration parameters, calibration performance, and the accuracy of the Meta-model is further discussed. The developed calibration platform in this study proved to have clear advantages over the existing platforms, with the ability to reasonably estimate building energy performance in a short computing time. © The Author(s) 2023.

关键词： Bayesian inference Building energy model Calibration Markov Chain Monte Carlo (MCMC) Sensitivity analysis Uncertainty

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IMPROVING APPLE OBJECT DETECTION WITH OCCLUSION-ENHANCED DISTILLATION

arXiv

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arXiv 2024年

作者： Geng, Liang Shi, Yuanping Ma, Yanheng Chu, Lina Li, Bingxuan Department of UAV Engineering Army Engineering University Shijiazhuang Campus Shijiazhuang050003 China College of Mechanical and Electrical Engineering Shijiazhuang University Shijiazhuang050035 China Shijiazhuang Key Laboratory of Agricultural Robotics Intelligent Perception Shijiazhuang050035 China

Apples growing in natural environments often face severe visual obstructions from leaves and branches. This significantly increases the risk of false detections in object detection tasks, thereby escalating the challenge. Addressing this issue, we introduce a technique called "Occlusion-Enhanced Distillation" (OED). This approach utilizes occlusion information to regularize the learning of semantically aligned features on occluded datasets and employs Exponential Moving Average (EMA) to enhance training stability. Specifically, we first design an occlusion-enhanced dataset that integrates Grounding DINO and SAM methods to extract occluding elements such as leaves and branches from each sample, creating occlusion examples that reflect the natural growth state of fruits. Additionally, we propose a multi-scale knowledge distillation strategy, where the student network uses images with increased occlusions as inputs, while the teacher network employs images without natural occlusions. Through this setup, the strategy guides the student network to learn from the teacher across scales of semantic and local features alignment, effectively narrowing the feature distance between occluded and non-occluded targets and enhancing the robustness of object detection. Lastly, to improve the stability of the student network, we introduce the EMA strategy, which aids the student network in learning more generalized feature expressions that are less affected by the noise of individual image occlusions. Our method significantly outperforms current state-of-the-art techniques through extensive comparative experiments. Copyright © 2024, The Authors. All rights reserved.

关键词： Students

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