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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Lin, Zheyuan Huang, Min Wang, Wen Qin, Mengjie Li, Te Wan, Minhong Gu, Jason Zhu, Shiqiang Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

For service robots, person re-identification (ReID) and multi-pedestrian tracking (MPT) are vital to get a person's location and link identities across frames. Though their accuracy keeps improving, most work lacks consideration of the application scenario, haunted by limited space, constrained power supply, and demands of the real-time response during human-robot interaction. Some ReID models learn trivial or unrelated features, inhibiting the downstream tasks. To solve these issues, the efficient and light-weighted Head-Shoulder Mask aided ResNet (HSMR) is proposed. This model applies multi-task learning to enhance the feature extraction performance in the training stage without extra computational load during inference. The auxiliary task fully uses head-shoulder information to guide the network and focuses on the head region, which contains the identity information. In experiments on the Tour-Guide Robot Data Base (TGRDB), HSMR earned results better than ResNet-18 on the ReID task and was superior to the recent two-stream method on the MPT task. On the mobile hardware, inference reaches an average of 15.2 FPS, three times faster than the two-stream method. The code is released at https://***/ZhYLin99/HSMR. © 2022 IEEE.

关键词： Human robot interaction

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Online Robot Motion Planning Methodology Guided by Group Social Proxemics Feature

arXiv

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arXiv 2025年

作者： Mu, Xuan Liu, Xiaorui Guo, Shuai Chi, Wenzheng Wang, Wei Ge, Shuzhi Sam School of Automation Qingdao University Qingdao266000 China School of Automation Qingdao University Qingdao University Qingdao266000 China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Suzhou215021 China School of Mechanical Engineering & Automation the Robotics Institute Beihang University Beijing100000 China Department of Electrical and Computer Engineering National University of Singapore Singapore117576 Singapore

Nowadays robot is supposed to demonstrate human-like perception, reasoning and behavior pattern in social or service application. However, most of the existing motion planning methods are incompatible with above requirement. A potential reason is that the existing navigation algorithms usually intend to treat people as another kind of obstacle, and hardly take the social principle or awareness into consideration. In this paper, we attempt to model the proxemics of group and blend it into the scenario perception and navigation of robot. For this purpose, a group clustering method considering both social relevance and spatial confidence is introduced. It can enable robot to identify individuals and divide them into groups. Next, we propose defining the individual proxemics within magnetic dipole model, and further established the group proxemics and scenario map through vector-field superposition. On the basis of the group clustering and proxemics modeling, we present the method to obtain the optimal observation positions (OOPs) of group. Once the OOPs grid and scenario map are established, a heuristic path is employed to generate path that guide robot cruising among the groups for interactive purpose. A series of experiments are conducted to validate the proposed methodology on the practical robot, the results have demonstrated that our methodology has achieved promising performance on group recognition accuracy and path-generation efficiency. This concludes that the group awareness evolved as an important module to make robot socially behave in the practical scenario. © 2025, CC BY-NC-ND.

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Preliminary Design and Performance Analysis of A Solar-Powered Jumping-Gliding Martian Aircraft

Preliminary Design and Performance Analysis of A Solar-Power...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Lou, Bin Xie, Anhuan Zhu, Shiqiang Liu, Yaru Gu, Jason Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

A solar-powered jumping-gliding Martian aircraft is proposed as a new tool for Mars exploration, designed especially to perform long-term wide-range detection. A completely new way of continues detection performed by aircraft is created. A preliminary design of the jumping-gliding Martian aircraft is carried out while its flight performance is analyzed afterwards. The conceptual design of a large-aspect ratio foldable wing with a thin fuselage and a jumping device is put forward. The solar energy model, aerodynamic model and weight mode are all built. The energy balance models are established for the periods of detecting mission that the aircraft lands on the ground for harvesting solar energy and flies in the sky. The gliding performance of this aircraft is particularly discussed here. © 2022 IEEE.

关键词： Aspect ratio

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Low-cost Mars Terrain Classification System Based on Coarse-grained Annotation

Low-cost Mars Terrain Classification System Based on Coarse-...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Zhang, Jian Chen, Yeheng Zhu, Shiqiang Li, Yuehua Xie, Tian Gu, Jason Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Dalhousie University Department of Electrical and Computer Engineering HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9781665481090

Due to communication latency with remote ground sites, automatic recognition of Mars terrain is essential for the path-planning of rovers. Currently, most vision-based terrain classification require thousands of fine-grained training samples, while the undefined terrains on Mars are difficult to be classified or fine-grained labeled. Actually, most of the terrain categories can only be coarse-grained labeled due to several limitations, such as overlapped sub-regions, blurred borders, etc. To solve this problem, CACMT (Coarse-grained Annotation-based Classification for Mars Terrain) is proposed to generate the global fine-grained classification map from the local coarse-grained data. Specifically, the complete pipeline is decomposed into (i) annotation rules with unique design, (ii) hierarchical feature fusion network for predicting sub-features of terrain (iii) and a generator for outputting dense terrain categories of Mars. Finally, the results of actual data on Mars demonstrate that the terrain sub-features can be successfully recognized and a dense terrain classification map can be generated applying only coarse-grained labeled images. © 2022 IEEE.

关键词： Motion planning

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Non-Rigid 3D Point Set Registration With Reliable Hybrid Mixture Model

Non-Rigid 3D Point Set Registration With Reliable Hybrid Mix...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Huang, Haocheng Zhang, Zhengyan Min, Zhe Meng, Max Q.-H. Song, Shuang Wang, Jiaole Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen518055 China Shandong University School of Control Science and Engineering Jinan250061 China Southern University of Science and Technology in Shenzhen Department of Electronic and Electrical Engineering China The Chinese University of Hong Kong Department of Electronic Engineering Hong Kong Shenzhen Research Institute of the Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9798350325706

Non-rigid point set registration is an essential technique in fields such as robotics, computer vision, image-guided surgery, and augmented reality. However, effectively addressing non-rigid deformations and handling noise interference remains a significant challenge in this context. This paper introduces a novel hybrid mixture model (HMM), combining a Gaussian mixture model (GMM) to describe positional features and a Fisher mixture model (FMM) to represent orientation features. This hybrid mixture model offers a solution to the non-rigid point set registration (PSR) problem. The proposed approach iteratively optimizes model parameters through the maximum expectation (EM) algorithm. It comprehensively explores registration performance, accounting for non-rigid deformations amidst isotropic and anisotropic positional noise. The proposed approach further incorporates reliable normal vectors for evaluating orientation features. Extensive experiments on non-rigid PSR demonstrates the improvements our algorithm offers in terms of both robustness and accuracy. © 2023 IEEE.

关键词： Nonrigid point set registration partial hybrid mixture model surgical navigation

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A Novel Three-Phase Passive Auxiliary Resonant Pole Soft-Switching Inverter With Symmetrical Auxiliary Networks and Electric Energy Feedback Function

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International Journal of Circuit Theory and Applications 2025年第0期

作者： Wang, Shuyu Liu, Hongchen Gao, Fei Wheeler, Patrick School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Department of Engineering Science Shanghai Jiao Tong University Shanghai China Power Electronics Machines and Control Research Institute University of Nottingham Santiago Chile

To solve the problems of high cost, large additional component size, large circulating loss, and complex control in existing auxiliary resonant soft-switching inverters, a three-phase passive auxiliary resonant pole inverter (ARPI) with symmetrical auxiliary networks and electric energy feedback function is proposed. On each phase bridge arm of the inverter, a set of passive auxiliary networks (PANs) without large electrolytic capacitors, transformers, and other devices is provided, which is capable of enhancing the power density of the inverter. Additionally, as the auxiliary commutation circuit does not employ auxiliary switches, it not only lowers the hardware cost but also simplifies the control complexity and enhances the reliability of the soft-switching inverter operation. The proposed topology is capable of enhancing the utilization ratio of DC voltage and reducing the harmonic content of the output waveform. According to the equivalent circuit diagrams in different operating modes, the soft-switching operating principle and realization conditions of soft-switching for the proposed ARPI are analyzed. The parameters of passive components are designed with the aim of minimizing the PAN loss. A 3-kW experimental prototype is constructed. The experimental results indicate that the switching tubes can realize the soft-switching action and suppress the rate of change of voltage and current. The efficiency of the prototype can reach 98.30% at the rated output power, which is a remarkable improvement compared with the same type of ARPIs. © 2025 John Wiley & Sons Ltd.

关键词： Poles

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Rock-Climbing Fish Inspired Skeleton-Embedded Rigid-Flexible Coupling Suction Disc Design for Adhesion Enhancement 16th

Rock-Climbing Fish Inspired Skeleton-Embedded Rigid-Flexible...

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

作者： Tan, Wenjun Qin, Hengshen Zhang, Chuang Wang, Ruiqian Zhang, Yiwei Yang, Lianchao Chen, Qin Wang, Feifei Xi, Ning Liu, Lianqing 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 Chengdu Institute of Biology Chinese Academy of Sciences Sichuan Chengdu610042 China Department of Electrical and Electronic Engineering University of Hong Kong 999077 Hong Kong Emerging Technologies Institute Department of Industrial and Manufacturing Systems Engineering University of Hong Kong Pokfulam999077 Hong Kong

ISBN: (纸本)9789819964888

Underwater high-performance biological adhesion systems have attracted increasing research interest to inspire engineered adhesion systems. Switchable underwater adhesion systems typically employ suction adhesion. However, achieving low pre-pressure negative pressure adhesion is still a challenge. An inspiring nature mode is provided by the rock-climbing fish, which needs little preload and can resist a pull-off force of 1000 times its own body weight. The pectoral and abdominal fins of rock-climbing fish have evolved to almost a flat suction cup. Through micro CT, we found that a unique skeletal network is embedded in the suction cup. This unique structure increases the stiffness of the suction cup and enhances its adhesion performance. Through numerical simulation, it was revealed that this rigid, flexible coupling structure enhances the ability of the suction cup to resist lateral pressure and increases the energy dissipation of the edge detachment of the suction cup. This work can shed light on the design of novel underwater adhesion systems and inspire underwater adhesion crawling robots. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Adhesion

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Dynamic Behavior of Levitated Flexible Steel Plate in Bending Electromagnetic Levitation System During Disturbance Input 27

Dynamic Behavior of Levitated Flexible Steel Plate in Bendin...

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27th International Conference on electrical Machines and Systems, ICEMS 2024

作者： Uchida, Yamato Ogawa, Kazuki Kobayashi, Ikkei Kuroda, Jumpei Uchino, Daigo Ikeda, Keigo Kato, Taro Endo, Ayato Narita, Takayoshi Kato, Hideaki Tokai University Course of Mechanical Engineering Kanagawa Hiratsuka Japan Aichi University of Technology Department of Electronics and Robotics Aichi Gamagori Japan National Institute of Standards and Technology Tokai University Kanagawa Hiratsuka Japan Research of Institute of Science and Technology Tokai University Kanagawa Hiratsuka Japan Numazu National College of Technology Department of Mechanical Engineering Shizuoka Numazu Japan Hokkaido University of Science Department of Mechanical Engineering Hokkaido Sapporo Japan Tokyo University of Technology Department of Mechanical Engineering Hachioji Tokyo Japan Fukuoka Institute of Technology Department of Electrical Engineering Fukuoka Fukuoka Japan Tokai University Department of Mechanical Systems Engineering Kanagawa Hiratsuka Japan

ISBN: (纸本)9784886864406

In thin steel plate production lines, contact conveying by rollers is used, which sometimes results in scratches and plating defects on the steel plate surface. To solve this problem, non-contact conveyance by magnetic levitation is expected. When thin steel plates are magnetically levitated, magnetic levitation control becomes difficult due to deflection caused by the flexibility of the plate. Therefore, we have proposed a curved magnetic levitation system that improves the levitation stability by curving the steel plate for magnetic levitation. However, the dynamic behavior of thin steel plates during bending magnetic levitation have not been clarified. In this report, we performed a levitation experiments of bending steel plate, and input disturbance to the bending levitation device. From the measured response of levitated and oscillated steel plate, it was confirmed that the bending thin steel plate was in rigid body motion due to the disturbance. © 2024 The institute of electrical Engineers of Japan.

关键词： Magnetic levitation

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Momentum-Imbued Langevin Dynamics (MILD) for Faster Sampling

Momentum-Imbued Langevin Dynamics (MILD) for Faster Sampling

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Nishanth Shetty Manikanta Bandla Nishit Neema Siddarth Asokan Chandra Sekhar Seelamantula Department of Electrical Engineering Indian Institute of Science Bangalore Department of Computer Science and Automation Indian Institute of Science Bangalore Microsoft Research Lab India (MSRI) Bangalore

Score-based generative models have emerged as the state-of-the-art in generative modeling. In this paper, we introduce a novel sampling scheme that can be combined with pre-trained score-based diffusion models to speed up sampling by a factor of two to five in terms of the number of function evaluations (NFEs) with a superior Fréchet Inception distance (FID), compared to Annealed Langevin dynamics in noise-conditional score network (NCSN) and improved noise-conditional score network (NCSN++). The proposed sampling algorithm is inspired by momentum-based accelerated gradient descent used in convex optimization techniques. We validate the sampling efficiency of the proposed algorithm in terms of FID on CIFAR-10 and CelebA datasets.

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Joint Class-Balanced Client Selection and Bandwidth Allocation for Cost-Efficient Federated Learning in Mobile Edge Computing Networks

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5681-5698页

作者： Tang, Jian Li, Xiuhua Li, Hui Li, Penghua Wang, Xiaofei Leung, Victor C. M. Chongqing University School of Big Data & Software Engineering Chongqing400000 China Chongqing University of Posts and Telecommunications School of Automation Chongqing400065 China Tianjin University College of Intelligence and Computing Tianjin300072 China Shenzhen MSU-BIT University Artificial Intelligence Research Institute Shenzhen518172 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of British Columbia Department of Electrical and Computer Engineering VancouverBCV6T1Z4 Canada

Federated Learning (FL) has significant potential to protect data privacy and mitigate network burden in mobile edge computing (MEC) networks. However, due to the system and data heterogeneity of mobile clients (MCs), client selection and bandwidth allocation is key for achieving cost-efficient FL in MEC networks with limited bandwidth. To address these challenges, we investigate the issue of joint client selection and bandwidth allocation for reducing the cost (i.e., latency and energy consumption) of FL training. We formulate the problem and decompose it into a holistic subproblem to reduce the number of rounds and a partial subproblem to reduce the costs of FL each round. We propose a joint class-balanced client selection and bandwidth allocation (CBCSBA) framework to address the whole problem. Specifically, for the holistic subproblem, CBCSBA combines MCs into groups, each having data distribution as close as possible to class-balanced distribution;For the partial subproblem, CBCSBA reduces costs by exploratively selecting a group and sequentially optimizing the latency and energy consumption of MCs within the group. Experimental results show that CBCSBA outperforms the baseline frameworks in reducing latency by 28.2% and energy consumption by 25.3% on average in the considered four datasets. © 2002-2012 IEEE.

关键词： Federated learning

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