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Personalized gait trajectory generation based on anthropometric features using Random Forest

Journal of Ambient Intelligence and Humanized Computing 2023年第12期14卷 15597-15608页

作者： Ren, Shixin Wang, Weiqun Hou, Zeng-Guang Chen, Badong Liang, Xu Wang, Jiaxing Peng, Liang The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China The CAS Center for Excellence in Brain Science and Intelligence Technology Beijing100190 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China

Using lower limb rehabilitation robots (LLRRs) to help stroke patients recover their walking ability is attracting more and more attention presently. Previous studies have shown that gait rehabilitation training with natural gait pattern can improve the therapeutic outputs. However, how to generate the personalized gait trajectory has not been well researched. In this paper, a personalized gait generation method based anthropometric features is proposed. Firstly, gait trajectories are fitted and simplified into Fourier coefficient vectors, which are used to represent gait trajectories. Secondly, fourteen body features are used to generate the personalized gait trajectories and the feature set is further optimized based on the minimal redundancy maximal relevance criterion for easy application on the LLRR. Then, the relationship between the optimized feature set and gait trajectories is modeled by using the RF algorithm. Finally, the performance of the proposed method is demonstrated by several comparison experiments. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Trajectories

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Homotopic Path Set Planning for Robot Manipulation and Navigation

arXiv

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arXiv 2024年

作者： Huang, Jing Tang, Yunxi Au, Kwok Wai Samuel Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Multi-Scale Medical Robotics Center Hong Kong

This paper addresses path set planning that yields important applications in robot manipulation and navigation such as path generation for deformable object keypoints and swarms. A path set refers to the collection of finite agent paths to represent the overall spatial path of a group of keypoints or a swarm, whose collective properties meet spatial and topological constraints. As opposed to planning a single path, simultaneously planning multiple paths with constraints poses nontrivial challenges in complex environments. This paper presents a systematic planning pipeline for homotopic path sets, a widely applicable path set class in robotics. An extended visibility check condition is first proposed to attain a sparse passage distribution amidst dense obstacles. Passage-aware optimal path planning compatible with sampling-based planners is then designed for single path planning with adjustable costs. Large accessible free space for path set accommodation can be achieved by the planned path while having a sufficiently short path length. After specifying the homotopic properties of path sets, path set generation based on deformable path transfer is proposed in an efficient centralized manner. The effectiveness of these methods is validated by extensive simulated and experimental results. Copyright © 2024, The Authors. All rights reserved.

关键词： Robot programming

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Development of Assembly Techniques for Miniaturized in-line Pressure Sensor by Utilizing Thin Strain Sensor for High Reliability

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IEEJ Transactions on Sensors and Micromachines 2024年第11期144卷 357-363页

作者： Ikeda, Hiroshi Kanamaru, Masatoshi Aono, Takanori Research & Development Group Connective Automation Innovation Center Robotics Research Department Hitachi Ltd. 832-2 Horiguchi Hitachinaka Ibaraki312-0034 Japan

High reliability assembly techniques for miniaturized in-line pressure sensor with diaphragm using a thin strain sensor have been developed to monitor the hydraulic pressure in the pipetting such as dispensing devices. The pressure sensor with a thin strain sensor as a diaphragm has two problems, (i) water leakage and (ii) sensitivity reduction by adding hydraulic pressure. These problems were clarified to generate tensile stress in the adhesive (Ag paste) by adding hydraulic pressure and to peel strain sensor from SUS housing. To overcome these problems, the stress in Ag paste was needed to keep compressive stress even when adding pressure. In this paper, a pressing mechanism is newly proposed to make compressive stress in Ag paste and assemble on the pressure sensor. First, to press the strain sensor to the SUS housing, a cap was bonded on the strain sensor with wafer-level-packaging (WLP) technique. Next, a pressing mechanism was designed to assemble on the miniaturized pressure sensor. The pressing mechanism was composed of a cover, two coil springs, and a spring base with pressing point. The pressing mechanism generates compressive stress to Ag paste even under high hydraulic pressure. The pressure sensor which implements the pressing mechanism has high pressure resistance and high reliability under the repetitive hydraulic pressure of 10 million times, without water leakage and sensitivity decrease. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Compressive stress

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Natural Disaster Damage Assessment using Semantic Segmentation of UAV Imagery

Natural Disaster Damage Assessment using Semantic Segmentati...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Muhammad Haroon Asad Malik Muhammad Asim Muhammad Naeem Mumtaz Awan Muhammad Haroon Yousaf Computer Engineering Department University of Engineering and Technology Taxila Pakistan Swarm Robotics Lab National Center of Robotics and Automation University of Engineering and Technology Taxila Pakistan

Numerous natural disasters due to climate change pose major threats to the sustainability of public infrastructure and human lives. For emergency rescue and recovery during a disaster, a rapid and accurate evaluation of disaster damage is essential. In recent years, the Transformer has gained popularity in a number of tasks related to computer vision, which offers tremendous potential for improving the accuracy of disaster damage assessments. Our research aims to determine whether Vision Transformer (ViT) can be used to assess natural disaster damage on high-resolution Unmanned Aerial Vehicle (UAV) data in comparison with conventional deep-learning semantic segmentation techniques. We discuss if Transformer can perform better than CNNs in accurately assessing the damage caused in order to bridge the gap. Detailed performance comparison of state-of-art deep learning semantic segmentation models (UNET, Segnet, PSPNet, Deeplabv3+) and Transformer framework (SegFormer) for damage assessment is presented. The experimentation is performed on both natural disaster damage datasets (RescueNet, FloodNet). The study supported SegFormer as the most appropriate model for estimating disaster damage, with mIoUs of 96% on the RescueNet dataset and 82.22% on the FloodNet dataset, respectively. The Transformer is capable of outperforming conventional segmentation CNNs in understanding the entirety of the scene and assessing the severity of the damage, based on both quantitative evaluation and visual results.

关键词： Industries Visualization Semantic segmentation Public infrastructure Random access memory Transformers Autonomous aerial vehicles

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Low-Cost 3D Holographic Display with Gesture Control 6

Low-Cost 3D Holographic Display with Gesture Control

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Bibi, Saima Imran, Ayesha Saud, Safwan Maheshwari, Mukesh Kumar Shankar Chowdhry, Bhawani Ejaz, Waleed Bahria University Karachi Campus Department of Electrical Engineering Karachi Pakistan Mehran University of Engineering & Technology National Center of Robotics & Automation Condition Monitoring Systems Lab Jamshoro Pakistan Lakehead University Department of Electrical Engineering BarrieON Canada

ISBN: (纸本)9798350333718

A way behind the past where teaching and learning were only by video, images, and 2D animations. Now we have live sessions where a classroom is bounded on just a laptop screen. What happened if that live session and 3D imaging are presented in the form of real sculpture by using Augmented Reality? In this paper, we are introducing a low-cost 3D display that presents both recorded and live sessions. Also, this display will be controlled with our fingertips. This application covers sectors of education, medical imaging, and advertisements with good effects and cheap cost. © 2023 IEEE.

关键词： Holograms

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Usability Evaluation of FURS Robot Control Panel Interface Design Based on SUS 16th

Usability Evaluation of FURS Robot Control Panel Interface D...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： You, Yong Wei, Lai Zhu, Shiqiang Yu, Yongwu Jiang, Yunxiang Liu, Xiaolei Han, Jianda Chen, Lingkai Song, Wei Design Innovation Center China Academy of Art Hangzhou310024 China L’École de Design Nantes Atlantique China Academy of Art Hangzhou310024 China Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Hangzhou Yunphant Network Technology Co. Ltd. Hangzhou China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China College of Artificial Intelligence and Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information Systems Nankai University Tianjin300350 China

ISBN: (纸本)9789819964949

The objective of this study is to compare the interfaces of two FURS (Flexible Ureterorenoscopy) robotic operation consoles across generations. Analyzing functional requirements during surgery, the first-generation interface was designed. Evaluation of the first-generation interface, combined with user needs and design principles, informed the design of the second-generation interface, which aimed to improve the usability of the console during surgery. Both interface generations were assessed for usability and user experience using the System Usability Scale (SUS).The results indicate improvement in usability and user satisfaction following interface iteration. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Surgery

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Towards Robo-Coach: Robot Interactive Stiffness/Position Adaptation for Human Strength and Conditioning Training

Towards Robo-Coach: Robot Interactive Stiffness/Position Ada...

引用

IEEE International Conference on robotics and automation (ICRA)

作者： Chenzui Li Xi Wu Tao Teng Sylvain Calinon Fei Chen Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Hong Kong Center for Logistics Robotics Hong Kong Idiap Research Institute Martigny Switzerland

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Traditional strength and conditioning training relies on the utilization of free weights, such as weighted implements, to elicit external stimuli. However, this approach poses a significant challenge when attempting to modify or adjust the loads within a single training set. This paper introduces an innovative method for achieving adjustable loads during resistance training by leveraging physical Human-Robot Interaction (pHRI). The primary objective is to regulate targeted muscle activation through the use of Robo-Coach (robotic coach system). We first utilize a Task-Parameterized Gaussian Mixture Model (TP-GMM) to learn the motion of coach demonstration, which can be generalized for the trainees. The 3D path extracted from the generated trajectory is then projected onto a 2D plane with respect to the direction of the load. Furthermore, we propose a hybrid stiffness/position generator for online task execution. This generator determines the desired positions in the 2D plane according to the contact point displacements in the stimuli direction and, simultaneously, sets the desired stiffness based on the muscle activation feedback. Finally, the Robo-Coach is implemented with a variable impedance controller to achieve load-adjustable resistance training with the trainee. The biceps curl exercises were conducted and the results showed favorable performance, indicating the effectiveness of this approach.

关键词： Training Three-dimensional displays Human-robot interaction Muscles Generators Trajectory Impedance

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Making Biometric Identification with EMG Easier: Using a Single Channel for Specific Purposes

Making Biometric Identification with EMG Easier: Using a Sin...

引用

International Conference on Advanced Electrical Engineering (ICAEE)

作者： Mehdi Chames Eddinne Layes Safia Benahmed Omar Kermia Electronics department Ecole National Polytechnique d'Alger Algiers Algeria Robotics and industrial automation Center for development of advanced technologies Algiers Algeria

ISBN: (数字)9798350349351

ISBN: (纸本)9798350349368

EMG has become a powerful method that was first used to identify muscle disorders in medical settings. Now, EMG signals are being used in a new way to identify people. Most biometric methods use complex systems with many channels, which makes them hard to use in real life. This study challenges this idea by suggesting that identification can be done with just one EMG channel for a smaller group of people. We explain how to collect, preprocess, and enhance data for EMG-based identification. We use a stacked Long Short-Term Memory (LSTM) neural network to classify EMG signals accurately and effectively. Our results show high accuracy and F1 scores equal to 96.4, which means our approach works well. This research not only improves EMG-based identification systems but also has potential uses in biometrics and other areas.

关键词： Electrical engineering Accuracy Biological system modeling Neural networks Muscles Biometric identification Electromyography Complex systems Long short term memory

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Neural Predictor for Flight Control with Payload

arXiv

引用

arXiv 2024年

作者： Jin, Ao Li, Chenhao Wang, Qinyi Liu, Ya Huang, Panfeng Zhang, Fan Research Center for Intelligent Robotics School of Automation Northwestern Polytechnical University Xi’an710072 China Research Center for Intelligent Robotics Shaanxi Province Innovation Team of Intelligent Robotic Technology School of Astronautics Northwestern Polytechnical University Xi’an710072 China

Aerial robotics for transporting suspended payloads as the form of freely-floating manipulator are growing great interest in recent years. However, the prior information of the payload, such as the mass, is always hard to obtain accurately in practice. The force/torque caused by payload and residual dynamics will introduce unmodeled perturbations to the system, which negatively affects the closed-loop performance. Different from estimation-like methods, this paper proposes Neural Predictor, a learning-based approach to model force/torque caused by payload and residual dynamics as a dynamical system. It results a hybrid model including both the first-principles dynamics and the learned dynamics. This hybrid model is then integrated into a MPC framework to improve closed-loop performance. Effectiveness of proposed framework is verified extensively in both numerical simulations and real-world flight experiments. The results indicate that our approach can capture force/torque caused by payload and residual dynamics accurately, respond quickly to the changes of them and improve the closed-loop performance significantly. In particular, Neural Predictor outperforms a state-of-the-art learning-based estimator and has reduced the force and torque estimation errors by up to 66.15% and 33.33% while using less samples. Copyright © 2024, The Authors. All rights reserved.

关键词： Predictive control systems

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A dexterous origami-inspired soft (DOIS) robot for objects reorientation and overturn

A dexterous origami-inspired soft (DOIS) robot for objects r...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Chen, Zhi Siu, Shipan Tin, Sinyee Liu, Yukhei Cao, Hanwen Gao, Yuan Zhou, Jianshu Liu, Yunhui Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong Center of Logistics Robotics

ISBN: (纸本)9781665436786

Soft robots have presented their potential for dexterous and smooth motion with inherent compliance, compact structure, and easy control over the traditional rigid robots. This paper presents a 3D printed origami-inspired soft robot (DOIS) robot, which is inspired by the zig-zag origami structure, capable of bi-lateral bending and linear extension/contraction in a compact structure. The motion range and dimension of DOIS robot are fully customizable. The actuation and control of DOIS robot are realized by two drive cables. Mounting a dedicated end-effector at the tip, the DOIS robot is capable of tackling challenges where robots need flexible motion such as object reorientation. We present two scenarios, egg reorientation and envelope flipping, to show the superiority of DOIS robot. The design, modeling, and control of DOIS robot are discussed in detail in this paper with related experimental validation. The proposed DOIS robot provides a practical solution for dexterous soft robot design. © 2021 IEEE.

关键词： End effectors

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