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第41届中国控制会议

作者： Xiaohong Li Zhicheng Li Zaiyue Yang Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineeringand the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in UniversitiesSouthern University of Science and Technology Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Bearing is a common and important component in the industry,and it is crucial to detect and diagnose its working *** to the characteristic the motion process of the bearing that is a periodic nonlinear system with sinusoidal input,a bearing fault detection method based on the nonlinear system with multi-frequency sinusoidal input is *** the dynamics modeling of the motion for the bearing,it is found that its input and output have the characteristics of almost periodic *** the periodogram-based asymptotic local fault detection method,the fault detection problem is transformed into a hypothesis test problem,and a threshold is obtained by the given confidence and the degree of freedom of a specific frequency *** method can effectively and quickly monitor the early minor faults in strong noise *** realization and performance of this bearing detection method are illustrated by the simulated vibration signal of the bearing.

关键词： Bearing dynamics model fault detection sinusoidal signal statistical methods

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Multiple Sensor Fusion-Based Positioning Robot for Steam Generator Inspection 2

Multiple Sensor Fusion-Based Positioning Robot for Steam Gen...

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2nd International Symposium on Sensor Technology and Control, ISSTC 2023

作者： You, Jingwei Wei, Shouqi Wu, Xiong Sun, Jianquan Guilin University of Electronic Technology Department of Electrical Engineering Guilin541004 China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518000 China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen518000 China

ISBN: (纸本)9798350314465

Nuclear energy is presently the clean energy source most likely to massively displace fossil energy, and the secondary side of the steam generator is an important part of a nuclear power plant. Due to the small space of the secondary side of the steam generator and the confinement of the vessel, the precise positioning of the robot inside the steam generator cannot be achieved by a single sensor alone. This paper introduces a multi-sensor fusion steam generator secondary side inspection robot. Primary emphasis is on data fusion of multiple sensors, such as laser sensors, cameras, IMU, and wheel encoder. First of all, this paper integrates data from wheel encoder data and IMU data by using extended Kalman filtering (EKF), which decreases the drift error during the motion and enhances the robot positioning precision. Afterwards, we incorporate laser ranging sensors and camera picture data to enhance the overall spatial sensitivity of the robot through particle filtering algorithms. Experiments show that the robot works reliably and has high positioning accuracy. © 2023 IEEE.

关键词： Steam generators

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Predict Hip Joint Moment Using CNN for Hip Exoskeleton Control 1

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

作者： Zhang, Yuanwen Xiong, Jingfeng Qian, Yuepeng Chen, Xinxing Guo, Yixuan Fu, Chenglong Leng, Yuquan Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen518055 China National University of Singapore Singapore117583 Singapore

ISBN: (数字)9789819964987

ISBN: (纸本)9789819964970

The assistance of the hip exoskeleton is closely related to hip joint moment, and the corresponding assistance can be generated by hip joint moment directly. However, it is difficult to obtain the hip joint moment directly from the sensor during walking. An effective method is to use deep learning models to predict hip joint moment using hip joint angle information. But there are still many challenges in applying this method to practical control systems. This study designs specific parameters to train a deep neural network for predicting hip joint moments and discusses the effects of the number of convolutional layers (N) and the length of sampling time (SL) on the prediction accuracy and the computation time in a real control system. Experiments show that for N ≤ 5, using angle information with SL ≤ 1.0 s achieves the highest prediction accuracy. However, for larger values of N (N > 5), the optimal SL becomes to be longer, where it increases to 2.0 s and the corresponding RMSE is 0.06260 Nm/kg and 0.05977 Nm/kg, respectively. These results indicate the importance of SL for prediction accuracy. Furthermore, a comparative analysis of the computation time with models using different N and SL is performed, and the relationship between computation time and prediction accuracy is discussed. This study provides specific model training parameters and detailed comparative analysis, which facilitates further application of deep learning models on hip exoskeletons. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Forecasting

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Design, Analysis, and Experiment of a Novel Ultrasonic Printing System

Design, Analysis, and Experiment of a Novel Ultrasonic Print...

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2022 IEEE International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale, 3M-NANO 2022

作者： Pei, Zhichao Zhao, Haoxiang Li, Dongjie Wang, Lefeng Rong, Weibin Sun, Lining Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin China

ISBN: (数字)9781665475433

ISBN: (纸本)9781665475433

Ultrasonic-driven printing technology is widely used in bioprinting because of its high precision, good biocompatibility, and low cost. However, the conventional ultrasonic printing technology still has problems such as cross-contamination of bio-ink during storage, transportation, and processing, and cumbersome ink replacement process. Therefore, a new ultrasonic printing device is developed in this paper, which uses PZT plates as the driving element. And a fluid sub-system has been fabricated based on the self-made glass micro-nozzle, which is connected to the drive element using ultrasonic couplant gel. The separation of the fluid system and the drive system has been realized through the modular design, thereby realizing the rapid replacement of different inks and this relatively independent fluid system is of great benefit to better sealing and aseptic operation. In addition, a digital model is built to analyze its working mechanism. And an experimental system is established to characterize the performance of the device. The results show that the system can generate droplets stably and accurately, and the droplet volume can be controlled by the excitation voltage amplitude and pulse width. © 2022 IEEE.

关键词： Biocompatibility

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Estimation and Prediction of CoM With Terrain Feature Embedding During Walking

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 16108-16120页

作者： Haolan Xian Jingfeng Xiong Yuanwen Zhang Xinxing Chen Chenglong Fu Yuquan Leng Key Laboratory of Biomimetic Robotics and Intelligent Systems Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China School of Biomedical Engineering and the State Key Laboratory of Robotics and Systems Harbin Institute of Technology (Shenzhen) Shenzhen China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China

Wearable devices are currently being used to reduce metabolism and assist people with disabilities for daily walking. For the elderly and disabled people, improving the walking stability of wearable devices is a crucial and unsolved research. In particular, the center of mass (CoM) trajectory can reflect the walking state as well as the stability of a person. For this reason, realizing the prediction of CoM trajectory under daily walking is promising to improve the wearable devices. In this article, a method for estimation and prediction of CoM during daily walking was proposed. A visual-inertial-odometry algorithm was used to obtain history CoM trajectories during walking, and the depth information from camera data was extracted by sequential distance embedding method and encode the information into terrain vectors. The trajectory vectors were patched with the corresponding terrain vectors and then realized the fusion of multi-modal data, which were then fed into a well-trained temporal convolution network to output the prediction results. With data from two outdoor datasets, the method in this paper was verified to be able to be used for CoM trajectory prediction for a variety of walking tasks and consume low computational cost. This method has the potential to be extensible in improving the stability of wearable devices, such as exoskeleton, powered prosthetic, and so on. Note to Practitioners—It is necessary to obtain the future state of human center of mass (CoM) to improve the stability of user with wearable devices. However, current methods for CoM trajectory prediction, especially with multi-modal data fusion are difficult to apply to this prediction task due to the high computational cost. This article addressed the problem of estimation and prediction of CoM under daily walking conditions and proposed a method to solve the above problems, which enable to deploy on wearable robots with limited computation resources. In our study, a visual-inertial-odometry

关键词： Trajectory Legged locomotion History Cameras Vectors Wearable devices Feature extraction Estimation Wearable robots Sensors

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Robotic Simulator with High-Precision Perception of Contact Dynamics

Robotic Simulator with High-Precision Perception of Contact ...

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IEEE International Conference on Development and Learning, ICDL

作者： Yongcan Zhou Yang Pan Tianjian Lei Junpeng Chen Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems and Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

A robotic simulator constitutes a pivotal tool in achieving accurate modeling and simulation within a virtual environment, especially concerning comprehensive robot training. This paper introduces a novel robotic simulator that employs a continuous compliant contact model, ensuring continuous and stable calculations during the contact process, with a specific focus on precise contact force computation during object collisions. The proposed physics engine captures energy transformations for diverse contact surface shapes and material properties, employing spring-dampers in collision detection. Dynamic equations are derived based on the spring stiffness system, damping coefficient, and external forces applied during the contact phase, enabling effective determination of dynamic parameters throughout the contact process, including position, velocity, and contact force during penetration. Experimental validation of the physics engine's contact solver involves investigating bouncing balls under varying coefficients of restitution. The conducted experiments successfully capture continuous variations in parameters such as contact force during the penetration process. The primary contribution of this paper lies in advancing physics engines to achieve accuracy in simulating and modeling virtual environments, particularly when applied to large-scale robot training. Beyond this context, the high-precision perception of contact dynamics within our robotic simulator bears potential implications in areas such as industrial automation, robotic manipulation, and virtual prototyping.

关键词：

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Enhancing Prosthetic Safety and Environmental Adaptability: A Visual-Inertial Prosthesis Motion Estimation Approach on Uneven Terrains

Enhancing Prosthetic Safety and Environmental Adaptability: ...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Chuheng Chen Xinxing Chen Shucong Yin Yuxuan Wang Binxin Huang Yuquan Leng Chenglong Fu Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Environment awareness is crucial for enhancing walking safety and stability of amputee wearing powered prosthesis when crossing uneven terrains such as stairs and obstacles. However, existing environmental perception systems for prosthesis only provide terrain types and corresponding parameters, which fail to prevent potential collisions when crossing uneven terrains and may lead to falls and other severe consequences. In this paper, a visual-inertial motion estimation approach is proposed for prosthesis to perceive its movement and the changes of spatial relationship between the prosthesis and uneven terrain when traversing them. To achieve this, we estimate the knee motion by utilizing a depth camera to perceive the environment and align feature points extracted from uneven terrains. Subsequently, an error-state Kalman filter is incorporated to fuse the inertial data into visual estimations to obtain a more robust and accurate estimation, which is then utilized to derive the motion of the whole prosthesis for our prosthetic control scheme. Experiments conducted on our collected dataset and stair walking trials with powered prosthesis show that the proposed method can accurately track the motion of human leg and the prosthesis with the average root-mean-square error of toe trajectory less than 5 cm. The proposed method is expected to enable the environmental adaptive control for prosthesis, thereby enhancing amputee’s safety and mobility in uneven terrains.

关键词： Legged locomotion Visualization Fuses Motion estimation Estimation Stairs Feature extraction Safety Kalman filters Prosthetics

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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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Different Height Stairs Climbing Pattern Generation for Humanoids

Different Height Stairs Climbing Pattern Generation for Huma...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Yang, Ming Tian, Dingkui Xu, Minjia Li, Feng Sun, Jianquan Shang, Weiwei Wu, Xinyu University of Science and Technology of China Hefei230026 China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China Daqing Vocational College Daqing163255 China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Shenzhen518055 China

ISBN: (纸本)9798350327182

Climbing stairs has been an indispensable ability for humanoids. This paper presents a novel and practical problem: climbing stairs of varying heights. In this study, the humanoid is modeled as an inverted pendulum and set the pelvis trajectory on the vertical axis, representing the center of mass (CoM), as a quadratic function. We also use a polynomial to design the ZMP and CoM trajectory on the horizontal plane. To generate the CoM trajectory, the sliding mode controller is utilized to track the reference trajectory. To eliminate chattering of the sliding mode controller, the universal approximation property of the radial basis function (RBF) network is leveraged to approximate the switching law. Finally, simulation experiments are performed in CoppeliaSim, and the biped robot is capable of walking stably and quickly. © 2023 IEEE.

关键词： Stairs

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Cam Profile Optimization for a Piezoelectric-Based Sole Energy Harvester

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

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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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