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检索条件"机构=Shenzhen Academy of Robotics of Robotics"

共 831 条记录，以下是81-90 订阅

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Motion Planning and Control with Environment Uncertainties for Humanoid Robot

Motion Planning and Control with Environment Uncertainties f...

引用

IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Zhiyong Jiang Jiawei Zhang Yu Wang Liyan Chen Jiangcheng Chen Siyu Wang Robotics Engineering Center the 21st Research Institute of China Electronics Technology Group Corporation Shenzhen Academy of Robotics (SZAR) Shenzhen Guangdong Province China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Humanoid robots are typically designed to function in static environments using markers and fixtures. To broaden their application, it is vital to understand environmental uncertainties, including kinematics and dynamics, and their interaction with unexpected external disturbances. Traditional robotic motion planning and control methods fall short of addressing these requirements. This study presents a perceptive motion temporal planning and control algorithm that enables humanoid robots to walk and operate safely in uncertain environments. Experiments validate the effectiveness of the developed algorithm, demonstrating its feasibility and advantages in controlling multiple robotic limbs synchronously with adaptability and robustness.

关键词： Robot motion Uncertainty Robot kinematics Dynamics Humanoid robots Aerospace electronics Robot sensing systems Planning Trajectory Synchronization

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An Autoencoder-Based Feature Extraction Method Applied to the Detection of Lateral Walking Gait Phase 1

引用

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

作者： Yang, Lijun Xiang, Kui Pang, Muye Luo, Mingxiang Yin, Meng Li, Wenju Cao, Wujing School of Automation Wuhan University of Technology Wuhan430070 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518005 China

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

The traditional method of extracting time-domain features is subjective and cumbersome. An autoencoder-based feature extraction method is proposed to overcome these shortcomings. Experiments were conducted to detect gait phases of lateral walking of 10 subjects at various gait cycles (rhythms) and strides, which combined into 9 lateral walking modes. Based on the stacked autoencoder with dropout (AE-dropout), different quantities of features from the original data were extracted. Subsequently, these features were used to detect the phase of lateral walking gait based on decision tree (Tree), k-Nearest Neighbors (KNN), support sector machines (SVM), and artificial neural network (ANN). The results demonstrated that the KNN, SVM, and ANN achieve higher accuracy after using the features extracted by our method for the detection of lateral walking gait phase. Moreover, with the increase of the number of extracted features, the cross-subject accuracy of the four models (AE-dropout + X, X represents Tree, KNN, SVM, and ANN) exhibit similar regularities, which increased first and then decreased. In addition, compared to the method of extracting time-domain features, our method has a smaller standard error of mean (SEM) in cross-subject recognition accuracy for different lateral walking modes. It proves that our method has greater generalization capabilities. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Feature extraction

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Research on Object Detection Methods in Low-Light Conditions 16th

Research on Object Detection Methods in Low-Light Conditio...

引用

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

作者： Wang, Feifan Chen, Xi’ai Wang, Xudong Ren, Weihong Tang, Yandong School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 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 University of Chinese Academy of Sciences Beijing100049 China Shenzhen518055 China

ISBN: (纸本)9789819964918

Low-light images are images taken in poorly illuminated environments. Such images suffer from colour distortion, loss of detail and blurriness, which seriously affects the detection accuracy of object detection tasks. In order to improve the accuracy of object detection in low-light images, we propose a low-light image object detection algorithm based on image enhancement. The algorithm is jointly trained on the input side of the YOLOv5 network in combination with an unsupervised low-light enhancement model. The training phase optimises the overall network with the loss of object detection so that the image enhancement results are more favourable for improving the object detection accuracy. In the feature extraction phase, we design a feature enhancement model based on an attention mechanism. Our algorithm is tested on the publicly available ExDark dataset and achieves a mean average precision (mAP) of 79.15%, which is a 4.25% improvement over the baseline. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Object detection

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Shape Optimization of Magnetorheological Brake for Performance Enhancement

Shape Optimization of Magnetorheological Brake for Performan...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Shi, Qiuyu Liu, Fajiang Wu, Xinyu Gao, Fei Southern University of Science and Technology Shenzhen518005 China Shenzhen Institute of Advanced Technology Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China

ISBN: (纸本)9781665481090

Magnetorheological (MR) rotary brakes leverage the magnetically controllable rheological properties of MR fluids to provide damping torque in lower limb assistance devices. This paper utilizes an optimization algorithm (Whale Optimization Algorithm (WOA)) to optimize the geometric dimension of the MR brake to enhance field-dependent brake torque. First, the mechanical design and optimization process of the MR brake were outlined. Then, the magnetic density of the MR fluid is evaluated using the ANSYS platform. With that, the WOA was exploited to optimize key design parameters across multiple iterations. According to the simulated results, the torque was improved from 17.39 Nm to 25.89 Nm, which increased by 48%. Finally, a prototype with the initial dimension was fabricated and preliminarily tested. © 2024 IEEE.

关键词： Shape optimization

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Modeling and control of a soft-rigid hybrid robotic glove for hand rehabilitation and assistance 12

Modeling and control of a soft-rigid hybrid robotic glove fo...

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022

作者： Jiang, Yongkang Shenzhen Institute of Advanced Technology Chinese Academy of Science Shenzhen518055 China Institute of Robotics Beihang University Beijing100191 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Soft robotic gloves have merits on assisting individuals with hand pathologies to perform continuous exercises to hand-functions restoration, which could accelerate the rehabilitation process and reduce costs. However, most of the soft gloves are composed of silicone-based actuators, whose time-consuming fabrication process and relatively low output force limit the development of soft robotic gloves. In this paper, we propose a novel design of a robotic glove based on soft-rigid hybrid joint actuators. We first introduce structures and working principles of each functional part of the glove in detail and then present the comprehensive theoretical modeling of the deformation and force response of the novel actuator which were experimentally validated. Furthermore, we evaluate the performances of the proposed robotic glove. The results show that the theoretical model can accurately predict the force-pressure response of the hybrid actuator. Besides, the proposed 10-DoF robotic glove is able to assist various training exercises and grasping various objects with different hand postures. This paper focuses on the modeling and control of a novel soft-rigid hybrid robotic glove, which will have an impact on the development of soft robots and wearable devices. © 2022 IEEE.

关键词： robotics

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Design and Signal Quality Assessment of a Novel Low-Cost Wireless EMG Sensor

Design and Signal Quality Assessment of a Novel Low-Cost Wir...

引用

IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Ziqin Ling Jiangcheng Chen Yaonan Li Ning Xi Department of Industrial and Manufacturing Systems Engineering University of Hong Kong Shenzhen Academy of Robotics Shenzhen China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Electromyography (EMG) sensors have been widely used for assessing muscle activation state and human-robot interaction (HRI). However, available commercial EMG sensors are expensive and inconvenient for real-time applications. The aim of this study is to design and validate a novel low-cost wireless EMG sensor. Specifically, the wireless EMG sensor is equipped with an analog-front-end (AFE), radio frequency (RF) module, and controller area network (CAN) bus, which achieves wireless data transmission and provides an interface for real-time HRI. The evaluation of the designed system was done by a series of exercises performed by volunteers. Raw signal., mean absolute value (MAV), zero crossings (ZC), slope sign changes (SSC), waveform length (WL), and median frequency (MDF) are used for comparing wireless EMG sensors and commercial sensors. In addition, Spearman's correlation (SC), and intra-class cross-correlation (ICC) are used as two validation indicators. The result shows that the SC and ICC between the raw signals of the two types of sensors are 0.6156 and 0.7780, respectively. The SC of MAV, ZC, SSC, WL, and MDF are 0.9708, 0.6740, 0.8023, 0.9663, and 0.9476, respectively. The ICC of MAV, ZC, SSC, WL, and MDF are 0.9670, 0.7340, 0.7910, 0.9540., and 0.8230, respectively. The results indicate a good agreement between the two systems and confirm the reliability of the wireless EMG sensor's design. The wireless EMG sensor can be further applied to real-time HRI and muscle fatigue assessment.

关键词： Wireless communication Wireless sensor networks Muscles Feature extraction Fatigue Electromyography Sensor systems Real-time systems Sensors Intelligent sensors

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Acquiring Large Field-of-View Optical Super-Resolution Images Using Adaptive As-Natural-As-Possible (AANAP) Image Stitching Method 13

Acquiring Large Field-of-View Optical Super-Resolution Image...

引用

13th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2023

作者： Sun, Hui Chen, Meng Wu, Cong Luo, Hao Chen, Qingjiu Jia, Boliang Zhang, Guanglie Li, Wen Jung City University of Hong Kong Department of Mechanical Engineering Hong Kong Hong Kong Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Shenzhen518000 China Hong Kong

ISBN: (纸本)9798350315196

Optical super resolution (OSR) is a technique that enhances the spatial resolution of images beyond the diffraction limit of the imaging system. OSR images can provide more details and information compared with conventional optical microscopes that are limited by the diffraction limit of light and thus have a best spatial resolution of about 200 nm. Moreover, the trade-off between magnification and field of view (FOV) hinders capturing large-scale structures and fine details simultaneously. Therefore, novel microscopy techniques that can overcome these limitations and provide high-resolution and large-FOV images of biological samples need to be developed. In this paper, a new method combining microsphere-based optical microscopic super-resolution imaging system and the image stitching method are proposed to improve the resolution and FOV conventional optical microscopy. First, the technique captures multiple images through the microsphere at different positions by moving the samples. Then, the technique stitches together the images using a registration algorithm to form a high-resolution, wide-field image. This technique can overcome the diffraction limit of optical microscopy and achieve sub wavelength resolution with a large FOV. It can be used in various fields of science and engineering, such as cell imaging, tissue imaging, and disease diagnosis. © 2023 IEEE.

关键词： Microspheres

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Cam Profile Optimization for a Piezoelectric-Based Sole Energy Harvester

Cam Profile Optimization for a Piezoelectric-Based Sole Ener...

引用

2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Liao, Haisu Ren, Zhongliang Wang, Yidi Wu, Xinyu Gao, Fei Southern University of Science and Technology Shenzhen518005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China

ISBN: (纸本)9781665481090

Harvesting energy from the human body to extend the operational time for low-power has gained significant attention. Recently, researchers have focused on biomechanical energy harvesting from human feet while walking. This paper presents an optimization of the cam profile for a piezoelectric-based sole energy harvester designed to be worn on the bottom of shoes to power electronic devices. Specifically, cams with linear polynomial and exponential functions were designed to actuate the piezoelectric transducers (PZTs). Force analysis revealed that the exponential function cam induces more significant deformation in the PZTs than the linear polynomial cam. Preliminary tests on a healthy subject validated this design, showing that the exponential function cam produced an average output power of 0.16mW at a walking speed of 5.5 km/h, indicating a 78% improvement over the linear polynomial cam. Moreover, the optimization rate increased with the growing walking speed. © 2024 IEEE.

关键词： Piezoelectric transducers

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Mitigating Hallucination in Visual Language Model Segmentation with Negative Sampling

Mitigating Hallucination in Visual Language Model Segmentati...

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International Symposium on Chinese Spoken Language Processing

作者： Tong Lee Chung Jun Cheng Jianxin Pang Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Research Institute of UBTech Robotics

ISBN: (数字)9798331516826

ISBN: (纸本)9798331516833

Recent advancements in Multi Modal Language Models (MMLMs) have led to major breakthroughs in object reasoning segmentation, which plays an important role in human robot interaction. However, hallucination arises when these systems encounter the task of segmenting non-existing objects, for example, when asked to segment a cat which does not appear in an image, the system will output a patch of false positive pixels. In this paper, we utilizes negative sampling approach to address this issue. Unlike other approaches that require acquiring new negative training data, our approach does not require any extra data and tuning of only a few hundred steps is needed. We conduct extensive experiments to identify hallucination in MMLM based segmentation systems and mitigate false positive pixel rate in Language Instructed Segmentation Assistant (LISA) by 50% while maintaining similar performance in existing object segmentation.

关键词： Training Image segmentation Visualization Computational modeling Large language models Training data Object segmentation Sampling methods Object recognition Tuning

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DualNet: Robust Self-Supervised Stereo Matching with Pseudo-Label Supervision 39

DualNet: Robust Self-Supervised Stereo Matching with Pseudo-...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Wang, Yun Zheng, Jiahao Zhang, Chenghao Zhang, Zhanjie Li, Kunhong Zhang, Yongjian Hu, Junjie City University of Hong Kong Hong Kong Chinese Academy of Sciences Institute of Automation CASIA China Zhejiang University China Sun Yat-sen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China The Chinese Univ of Hong Kong Shenzhen China

ISBN: (纸本)157735897X

Self-supervised stereo matching has drawn attention due to its ability to estimate disparity without needing ground-truth data. However, existing self-supervised stereo matching methods heavily rely on the photo-metric consistency assumption, which is vulnerable to natural disturbances, resulting in ambiguous supervision and inferior performance compared to the supervised ones. To relax the limitation of the photo-metric consistency assumption and even bypass this assumption, we propose a novel self-supervised framework named DualNet, which consists of two key steps: robust self-supervised teacher learning and pseudo-label supervised student training. Specifically, the teacher model is first trained in a self-supervised manner with a focus on feature-metric consistency and data augmentation consistency. Then, the output of the teacher model is geometrically constrained to obtain high-quality pseudo labels. Benefiting from these high-quality pseudo labels, the student model can outperform its teacher model by a large margin. With the two well-designed steps, the proposed framework DualNet ranks 1st among all self-supervised methods on multiple benchmarks, surprisingly even outperforming several supervised counterparts. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Self-supervised learning

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