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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Huang, Jingchen Fang, Yun Guo, Weichao Qiao, Zhijian Sheng, Xinjun School of Mechanical Engineering Meta Robotics Institute Shanghai Jiao Tong University State Key Laboratory of Mechanical System and Vibration Shanghai200240 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong

ISBN: (纸本)9781665481090

Communicating information to users is a crucial aspect of human-machine interaction. Vibrotactile feedback encodes information into spatiotemporal vibrations, enabling users to perceive tactile sensations. It offers advantages such as lightweight, wearability, and high stability, with broad applications in sensory substitution, virtual reality, education, and healthcare. However, existing haptic unit designs lack amplitude modulation capabilities, which limits their applications. This paper proposed an optimized design of the haptic unit from the perspective of vibration amplitude modulation. A modified elastic model was developed to describe the propagation and attenuation mechanisms of vibration in the skin. Based on the model, two types of hierarchical architectural design were proposed. The design incorporated various materials arranged in multiple layers to amplify or attenuate the vibration amplitude as it traveled through the structure. An experimental platform was built to evaluate the performance of the optimized design. © 2024 IEEE.

关键词： Virtual reality

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A Genderless Docking Mechanism with Passive Locking and High Rotation Misalignment Tolerance for Modular Space Robots

A Genderless Docking Mechanism with Passive Locking and High...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Chen, Jian Wen, Xiaodong Wang, Hao Gong, Wei Deng, Zongquan Yu, Haitao Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China Tianjin Institute of Aerospace Mechanical and Electrical Equipment Tianjin Key Laboratory of Aerospace Intelligent Equipment Technology Tianjin China

ISBN: (纸本)9781665481090

Modular robots are gaining increasing attention in space services. The docking mechanism plays a critical role in performing self-healing and self-reconfiguration of modular robots. It is beneficial for the docking mechanism to operate with high efficiency, homogeneity and high misalignment tolerances. To meet these requirements, this paper presents a novel genderless docking mechanism. The construction of the docking mechanism is designed with features of passive locking and single-sided electromagnetic unlocking. To demonstrate the advantages of passive locking, the working processes of the axial and circumferential locking mechanisms are described in detail. Based on theoretical calculations and simulations, it is shown that the docking mechanism can provide fast connections or disconnections with a degree of translational and angular misalignment tolerances. This docking mechanism is intended for future applications in modular space robots or unstructured environment exploration robots. © 2022 IEEE.

关键词： Modular robots

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Dynamic Object Removal of Static 3D Point-Cloud Map Building in Casualty Collection Point

Dynamic Object Removal of Static 3D Point-Cloud Map Building...

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International Conference on Control, Automation, robotics and Vision (ICARCV)

作者： Haidong Wang Wanlei Li Yijie Dai Xiaogang Xiong Yunjiang Lou State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology ShenZhen Shenzhen China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Understanding the environment is crucial for the autonomous navigation of vehicles. Accurately identifying and removing dynamic objects that cause occlusions and noisy pose issues is crucial to the task. The casualty collection point (CCP) is a designated location for treating casualties during disasters. These sites are commonly located in open fields to ensure that the injured receive timely and appropriate care. Therefore, the construction of a 3D map in CCP may encounter additional challenges. In this paper, we introduces a novel algorithm that integrates a learning-based multi-object detection network with a Kalman Filter tracking framework to remove dynamic object traces from the 3D map building, particularly in CCP scenarios, and it redirects attention on the velocity attribute of dynamic objects at the object-level scale. Additionally, we contribute a new dataset specifically designed for the CCP scenario. Comparative experiments conducted on the SemanticKITTI dataset and CCP dataset show that our proposed method achieves the state-of-the-art performance in removing traces of dynamic objects on 3D Map. Dataset is available at https://***/haidongwang96/ccp_dataset.

关键词： Point cloud compression Three-dimensional displays Simultaneous localization and mapping Heuristic algorithms Buildings Object detection Kalman filters Object recognition Noise measurement Vehicle dynamics

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Smart Plant Application of Autonomous Decentralized systems with the Introduction of Edge Nodes 15

Smart Plant Application of Autonomous Decentralized Systems ...

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15th International Conference on Advanced Computer Theory and Engineering, ICACTE 2022

作者： Wang, Jingyang Zou, Tao Yang, Zhijia Wang, Hongrui Key Laboratory Of Networked Control System Institutes For Robotics And Intelligent Manufacturing Shenyang Institute Of Automation Chinese Academy Of Sciences Shenyang China Guangzhou University College Of Mechanical And Electrical Engineering Guangzhou China State Key Laboratory Of Robotics Key Laboratory Of Networked Control System Institutes For Robotics And Intelligent Manufacturing Shenyang Institute Of Automation Chinese Academy Of Sciences Shenyang China University Of Chinese Academy Of Sciences Beijing China

ISBN: (数字)9781665481809

ISBN: (纸本)9781665481809

This paper illustrates the application of an autonomous decentralized system introducing edge nodes in a smart factory. The nodes include atomic nodes, the most fundamental autonomic units constituting an autonomous decentralized system that are capable of independently extracting information from the data field and processing that information internally and simultaneously transmitting the processing results and other internal information to the data field proactively in a broadcast mode, where the transmitted information circulates in the data field. The group-based data field enables the sharing of information by atomic nodes. Grouped management nodes are the managers of the whole group, and edge nodes are the terminal intelligent control units of an intelligent autonomous decentralized system. Improvements in system decentralization, fault tolerance characteristics and flexibility of the system can lead to homogenization, autonomous control and autonomous coordination in complex manufacturing environments, as well as excellent online fault tolerance, online expansion and online maintenance of the system. In addition, it enhances the ever-changing and evolving control requirements by deconstructing the complexity in the system. © 2022 IEEE.

关键词： Fault tolerance

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Mag-Boost Mechanism for High-Power Ocean Wave Energy Harvesting

SSRN

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SSRN 2024年

作者： Tang, Tianyi Li, Yunfei Huang, Manjuan Mei, Mingqi Wang, Zizhao Zha, Fusheng Sun, Lining Liu, Huicong School of Mechanical and Electrical Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou215123 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

Ocean wave energy is a highly anticipated renewable energy source. However, due to the ultra-low frequency and random characteristics of ocean waves, efficient and high-power energy harvesting has been a great challenge. By ingeniously leveraging the phenomenon of sudden magnetic-torque variation in orthogonal magnetic fields, this paper proposes an innovative Mag-Boost mechanism, which is capable of converting ultra-low excitation below 1Hz to high-frequency oscillations of power-magnet more than 50Hz without direct contact. The energy conversion efficiency of this mechanism can be as high as 89.3%. By integrating four Mag-boost units into a circular array, a high-power wave energy harvester (WEH) with ultra-low frequency response capabilities has been proposed. At a frequency of 1Hz and an inclination angle of 30°, the WEH demonstrated a high output performance with power of 1.79W and power density of 1.88kW/m³, which is an order of magnitude higher than those of the previous reported ones. During the off-shore test at Yellow Sea, the WEH reached the peak open-circuit voltage of 10V, ensuring completely independent and stable power supply for wireless temperature and humidity sensors. Furthermore, the Mag-Boost mechanism also shows considerable potential for harvesting other forms of low-frequency environmental energy, including wind, vibration, and human kinetic energy. © 2024, The Authors. All rights reserved.

关键词： Water waves

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Squeezing More Past Knowledge for Online Class-Incremental Continual Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 722-736页

作者： Da Yu Mingyi Zhang Mantian Li Fusheng Zha Junge Zhang Lining Sun Kaiqi Huang the State Key Laboratory of Robotics and System Harbin Institute of Technology(HIT)Harbin 150080China Center for Research on Intelligent System and Engineering Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent System and Engineering Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190the School of Artificial IntelligenceUniversity of Chinese Academy of SciencesBeijing 100049 the CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai 200031China IEEE

Continual learning(CL)studies the problem of learning to accumulate knowledge over time from a stream of data.A crucial challenge is that neural networks suffer from performance degradation on previously seen data,known as catastrophic forgetting,due to allowing parameter *** this work,we consider a more practical online class-incremental CL setting,where the model learns new samples in an online manner and may continuously experience new ***,prior knowledge is unavailable during training and *** works usually explore sample usages from a single dimension,which ignores a lot of valuable supervisory *** better tackle the setting,we propose a novel replay-based CL method,which leverages multi-level representations produced by the intermediate process of training samples for replay and strengthens supervision to consolidate previous ***,besides the previous raw samples,we store the corresponding logits and features in the ***,to imitate the prediction of the past model,we construct extra constraints by leveraging multi-level information stored in the *** the same number of samples for replay,our method can use more past knowledge to prevent *** conduct extensive evaluations on several popular CL datasets,and experiments show that our method consistently outperforms state-of-the-art methods with various sizes of episodic *** further provide a detailed analysis of these results and demonstrate that our method is more viable in practical scenarios.

关键词： Catastrophic forgetting class-incremental learning continual learning(CL) experience replay

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A Novel Gait Pattern Recognition Method Based on LSTM-CNN for Lower Limb Exoskeleton

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Journal of Bionic Engineering 2021年第5期18卷 1059-1072页

作者： Chao-feng Chen Zhi-jiang Du Long He Yong-jun Shi Jia-qi Wang Wei Dong State Key Laboratory of Robotics and System Harbin Institute of Technology(HIT)Harbin 150001China China South Industries Group Corporation Weapon Equipment Research InstituteBeijing 102202China

This paper describes a novel gait pattern recognition method based on Long Short-Term Memory(LSTM)and Convolutional Neural Network(CNN)for lower limb *** Inertial Measurement Unit(IMU)installed on the exoskeleton to collect motion information,which is used for LSTM-CNN *** article considers five common gait patterns,including walking,going up stairs,going down stairs,sitting down,and standing *** the LSTM-CNN model,the LSTM layer is used to process temporal sequences and the CNN layer is used to extract *** optimize the deep neural network structure proposed in this paper,some hyperparameter selection experiments were carried *** addition,to verify the superiority of the proposed recognition method,the method is compared with several common methods such as LSTM,CNN and *** results show that the average recognition accuracy can reach 97.78%,which has a good recognition eff ***,according to the experimental results of gait pattern switching,the proposed method can identify the switching gait pattern in time,which shows that it has good real-time performance.

关键词： Lower limb exoskeleton Gait pattern recognition LSTM-CNN Recognition accuracy Real-time performance

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NNPP: A Learning-Based Heuristic Model for Accelerating Optimal Path Planning on Uneven Terrain

arXiv

引用

arXiv 2023年

作者： Ji, Yiming Liu, Yang Xie, Guanghu Ma, Boyu Xie, Zongwu Cao, Baoshi State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China

Intelligent autonomous path planning is essential for enhancing the exploration efficiency of mobile robots operating in uneven terrains like planetary surfaces and off-road environments. In this paper, we propose the NNPP model for computing the heuristic region, enabling foundation algorithms like A* to find the optimal path solely within this reduced search space, effectively decreasing the search time. The NNPP model learns semantic information about start and goal locations, as well as map representations, from numerous pre-annotated optimal path demonstrations, and produces a probabilistic distribution over each pixel representing the likelihood of it belonging to an optimal path on the map. More specifically, the paper computes the traversal cost for each grid cell from the slope, roughness and elevation difference obtained from the digital elevation model. Subsequently, the start and goal locations are encoded using a Gaussian distribution and different location encoding parameters are analyzed for their effect on model performance. After training, the NNPP model is able to accelerate path planning on novel maps. Experiments demonstrate that the heuristic region generated by the NNPP model achieves a 3×speedup for optimal path planning under identical hardware conditions. Moreover, the NNPP model’s advantage becomes more pronounced as the size of the map increases. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Inverse Kinematics of a Reconfigurable Space Manipulator Based on the Closed-Loop Algorithm

Inverse Kinematics of a Reconfigurable Space Manipulator Bas...

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IEEE International Conference on Mechatronics and Automation

作者： Zhiyuan Zhao Xiaohang Yang Zichun Xu Yuntao Li Zhonglai Tian Jingdong Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang Province China

This paper investigates a reconfigurable space manipulator’s inverse kinematics (IK) with two lockable passive telescopic links (LPTLs). Depending on these LPTLs’ locking state, the manipulator includes free-space and reconfiguration operation modes. Firstly, we introduce a new ball joint-based solution for the reconfigurable operation mode. Then, we propose an IK simplified method capable of significantly reducing the computational load of the complex inverse differential kinematic (IDK) equations corresponding to the two operation modes. Next, to solve the resulting simplified IDK equations efficiently, we present an IK solution method based on the closed-loop algorithm. This method is developed to resolve the redundancy at the velocity level and can generate highly accurate and smooth trajectory IK solutions that satisfy the joint limit constraints. Finally, we design two typical case studies corresponding to working scenarios of the manipulator during two operation modes. Their simulation results validate the proposed methods’ effectiveness.

关键词：

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Review:Wearable Sweat Sensors for Diseases Prevention and Monitoring

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Journal of Harbin Institute of Technology(New Series) 2023年第3期30卷 1-21页

作者： Yanan Ding Haiying Xiao Ping’an Hu School of Chemistry and Chemical Engineering Harbin Institute of TechnologyHarbin 150080China MOE Key Lab of Micro-System and Micro-Structures Manufacturing Harbin Institute of TechnologyHarbin 150080China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150080China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150080China

Advanced in wireless technologies and flexible materials with great biocompatibility,wearable devices have been utilized in the field of healthcare,sports management,and diseases prevention,which have been widely applied in current electronic ***,as a common metabolite on the skin surface,contains a wealth of biomarkers for disease detection and ***,developing wearable sweat sensors can provide a non⁃invasive method for health data collecting,sports monitoring,and clinical diagnosis in a convenient *** research in sweat metabolomics has offered a lot of information for sweat analysis and the wearable sweat sensors with small size,various sensing,and transmission units,and good skin contact has exhibited dynamic multi⁃signal *** article introduces the biomarkers in sweat related to different diseases and the current development of sweat sensors for user􀆳s activation monitoring and diseases *** barriers and difficulties in the future are also discussed and perspectives in the next generation sweat sensors are proposed.

关键词： sweat sensor sweat metabolites disease monitoring wearable device

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