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Fifth International Conference on advanced robotics - '91 ICAR

作者： Sagisawa, Sinobu Advanced Robot Technology Research Association: ARTA Minato Tokyo Japan

ISBN: (纸本)0780300785

A Japanese National Research and Development Project aimed at realization of next generation robots and cultivation of elementary technology for advanced robots was finished successfully in 1990. An outline of the project is given, and three robots are presented. One is for maintenance, inspection and repair in nuclear power plants; one is for similar functions in offshore oil facilities; and one is for fire-fighting, fire prevention and rescue in petrochemical facilities. All are supported by a remote operator.< >

关键词： Research and development Service robots Orbital robotics Medical robotics Mining industry Large-scale systems US Department of Transportation Aerospace industry Safety Temperature distribution

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From Concept to Field Trials: Design, Analysis, and Evaluation of a Novel Quadruped robot with Deformable Wheel-Foot Structure

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IEEE Transactions on robotics 2025年 41卷 3143-3161页

作者： Ju, Zhongjin Wei, Ke Xu, Yundou Yanshan University Parallel Robot and Mechatronic System Laboratory of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Advanced Forging and Stamping Technology and Science Ministry of Education of China Qinhuangdao066004 China

This study introduces a novel quadruped robot, the TerraAdapt, furnished with an innovative deformable wheel-foot integrated structure. This unique design grants the robot the flexibility to alternate between wheeled and footed modes of locomotion, making it efficient in traversing diverse terrains, from smooth indoor floors to challenging outdoor landscapes laden with obstacles. The study delineates an in-depth design and analysis of the deformable wheel and its integrated wheel-foot structure using screw theory. We engineer a 2RRR-RP wheel-foot mode-switching mechanism by modifying a 2RRR spatial six-bar mechanism with an additional RP branch. This mechanism aids in seamless transitioning between different movement modes. Moreover, a 2RRR parallel structure is employed to construct the footed mode *** substantiate the viability and efficacy of the proposed design, we carry out extensive motion simulations and construct an experimental prototype for field testing. The field trials reveal the robot's adeptness in adapting to varied terrains, highlighting the possible advantages of incorporating the proposed deformable wheel into micro mobile robot designs. © 2004-2012 IEEE.

关键词： Machine design

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GCN Rewarded Reinforcement Learning for Action Segmentation 24

GCN Rewarded Reinforcement Learning for Action Segmentation

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4th International Joint Conference on robotics and Artificial Intelligence, JCRAI 2024

作者： Wang, Liangliang Liu, Jiayao Hu, Xujun Huo, Guanglei Wuhan University of Technology Wuhan China Beijing Jiaotong University Beijing China Institute of Advanced Manufacturing Technology Fujian Key Laboratory of Intelligent Operation and Maintenance Robot Technology Quanzhou China

ISBN: (纸本)9798400710100

Action recognition is a very basic topic for human-robot visual interaction. To enable action recognition for real-world applications, at the core is the problem of action segmentation, which aims to segment action slices from long videos. Existing action segmentation approaches rely heavily on hand-crafted techniques, which are limited on accuracy due to the spatio-temporal complexity of actions across videos. To this end, we formulate action segmentation as a Markov decision process rewarded by observing the action recognition results, and build a reinforcement learning framework to adjust the segmenting procedure iteratively according to the rewards. In particular, to perceive the segmented actions for reinforcement learning, we propose a temporal graph convolutional network (GCN) by representing the context relationships of neighboring action slices, whose states are initialized by considering the consistency of actions, and updated by computing their temporal similarity fusing the tIoU and center distance. Convolutional neural network (CNN) backbone features are used as the nodes of GCN, and the edges of GCN are calculated utilizing the context relationships for spatially and temporally representation. By designing an observation and objective module within the reinforcement learning framework based on GCN representations, we finish the network training for. Finally, we conduct extensive experiments on two public datasets, and by comparisons with some state-of-the-art results, our method is demonstrated. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Convolutional neural networks

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Study on the wear resistance of 2024-T351 aluminum alloy strengthened by ultrasonic-assisted laser shock peening

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Journal of Materials Science 2025年第13期60卷 5954-5976页

作者： Meng, Xiankai Cheng, Zilong Zhou, Jianzhong Song, Fuyang Zhao, Xianhua Wu, Wei Gao, Fei Cai, Jie Xue, Wei Liu, Yang Institute of Advanced Manufacturing and Modern Equipment Technology Jiangsu University Zhenjiang212013 China School of Mechanical Engineering Jiangsu University Zhenjiang212013 China Department of Research and Development Shandong Huawin Electrica and Mechanical Technology Co. Ltd Jinan250098 China International Science & Technology Cooperation Base for Laser Processing Robot Wenzhou University Wenzhou325035 China

The ultrasonic-assisted laser shock peening (ULP) technique, through the combined strengthening effects of laser shock peening and ultrasonic peening, can enhance the wear resistance and fatigue resistance of metal materials. This paper uses the 2024-T351 aluminum alloy as the subject for ULP enhancement experiments. Comprehensive tests including microstructure, phase structure, surface morphology, microhardness, residual stress, and wear resistance were conducted. Furthermore, coefficient of friction (COF), wear volume loss, and wear morphology were analyzed to reveal the improvements in wear resistance and the transformations in wear mechanisms induced by ULP treatment. Significant grain refinement and high-density dislocations are induced by ULP treatment, which results in pronounced work hardening effects, achieving a surface microhardness of 191.9 HV and a hardened layer depth of 850 µm. Compared to the untreated samples, the high-hardened surface induced by ULP reduces the possibility of material peeling from the surface, leading to a decrease in average COF and wear volume loss by up to 37.9% and 40.8%, respectively. Additionally, the ULP treatment effectively suppress adhesive wear, significantly improving the wear morphology and enhancing the wear resistance of the aluminum alloy. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Grain refinement

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Predictive Control for an Ankle Rehabilitation robot Using Differential Evolution Optimization Algorithm-Based Fuzzy NARX Model

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IEEE Transactions on Neural Systems and Rehabilitation Engineering 2025年 33卷 1888-1897页

作者： Xie, Shenglong Zhong, Haiming Li, Yuntang Xu, Su'an Liu, Wenyuan Bian, Shiyuan Zhang, Shiwu China Jiliang University School of Mechanical and Electrical Engineering Zhejiang Hangzhou 310018 China University of Science and Technology of China School of Engineering Science Department of Precision Machinery and Precision Instrumentation Institute of Humanoid Robots Hefei 230026 China Anhui Key Laboratory of Bionic Sensing and Advanced Robot Technology Hefei 230031 China

For patients with stroke, hemiplegia and ankle injuries, ankle rehabilitation robots can provide personalized rehabilitation treatment programs through quantitative evaluation and precise control. In this paper, based on differential evolution (DE) optimization algorithm and fuzzy nonlinear auto regressive with exogenous inputs (NARX) model, an iterative learning model predictive controller is constructed to achieve accurate and robust trajectory tracking control of an ankle rehabilitation robot driven by pneumatic muscle. Firstly, the T-S fuzzy NARX model is applied to characterize the forward and inverse hysteresis process of pneumatic muscle actuator (PMA) in this ankle rehabilitation robots and differential evolution optimization (DE) algorithm realize high precision parameters identification. Then, the optimization of objective function is compared with genetic algorithm and particle swarm optimization. Secondly, the iterative learning model predictive control (ILMPC) controller is designed and the trajectory tracking control scheme of an ankle rehabilitation robot is presented based on the ILMPC controller. Finally, the experiments with different trajectories and subjects are carried out to verify the control performance of the proposed control method. The experimental results indicate that the proposed ILMPC controller can converge normally and has good control performance with different operating trajectories and subjects. © 2001-2011 IEEE.

关键词： differential evolution (DE) iterative learning model predictive control (ILMPC) Pneumatic muscle actuator (PMA) T-S fuzzy NARX model

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Research on path planning of mobile robots based on improved A* algorithm

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PeerJ Computer Science 2025年 11卷 e2691-e2691页

作者： Fu, Xing Huang, Zucheng Zhang, Gongxue Wang, Weijun Wang, Jian Robot and Intelligent Equipment Center Guangzhou Institute of Advanced Technology Guangdong Guangzhou China College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Shaanxi Xi’an China

To address the issues of low search efficiency, excessive node expansion, and the presence of redundant nodes in the traditional A* algorithm, this article proposes an improved A* algorithm for mobile robot path planning. Firstly, a multi-neighborhood hybrid search method is introduced, optimizing the traditional eight-neighborhood and twenty-four-neighborhood into a new sixteen-neighborhood. The choice between eight-neighborhood search and sixteen-neighborhood search is determined based on the presence of obstacles in the eight-neighborhood around the current node, effectively enhancing the search efficiency of the algorithm and reducing the number of nodes expanded during the search process. Subsequently, unnecessary nodes are eliminated based on the positional relationship between the current node and the target node, according to neighborhood direction search rules, further decreasing the number of expanded nodes. Additionally, improvements to the bidirectional search mechanism along with the incorporation of dynamic weight coefficients further enhance the search efficiency of the algorithm. Furthermore, a strategy for extracting key nodes is employed to effectively remove useless turn points, thus resolving the issue of redundant nodes. Finally, simulation experiments demonstrate that the proposed improved A* algorithm outperforms the traditional A* algorithm in terms of search speed, number of expanded nodes, and path length, validating the effectiveness of the proposed method. Copyright 2025 Fu et al. Distributed under Creative Commons CC-BY 4.0

关键词： Motion planning

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The research of distributed CO2 monitoring technology based on NB-IoT 4

The research of distributed CO2 monitoring technology based ...

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4th International Computational Imaging Conference, CITA 2024

作者： Hu, Chun Li, Yanlin Zheng, Dezhi Cheng, Yufei Peng, Peng Nie, Sichong Advanced Research Institute of Multidisciplinary Sciences Beijing Institute of Technology Beijing100081 China MIIT Key Laboratory of Complex-field Intelligent Exploration Beijing Institute of Technology Beijing100081 China State Key Laboratory of CNS/ATM Beijing Institute of Technology Beijing100081 China Chongqing Caeri Robot Technology Co. Ltd. Certification Department Chongqing400722 China Innovation&Research Institute of HIWING Technology Academy Beijing100074 China

ISBN: (纸本)9781510688834

CO2 is one of the primary contributors to the greenhouse effect, and its monitoring and control are critical for achieving carbon peaking and neutrality goals. Therefore, large-scale distributed monitoring of CO2 concentrations in the environment is of significant importance. To investigate the diffusion patterns of CO2 in windless environments, this paper designs and implements a distributed CO2 monitoring system. The system adopts the three-layer architecture of the Internet of Things (IoT) as its overall framework, utilizing a self-developed CO2 sensor as the sensing layer node. The system employs the Narrowband Internet of Things (NB-IoT) protocol to achieve multi-node, wide-coverage, and low-power data transmission and reception. A custom database is developed as the application layer to store, classify, and manage data collected by the nodes. Experimental results provide CO2 monitoring data, which are analyzed to summarize the variation patterns of CO2 concentration over time and distance. By comparing these results with existing gas diffusion models, it is found that the trends are consistent, thereby demonstrating the reliability and stability of the proposed system. © 2025 SPIE.

关键词： Carbon capture and utilization

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RGB-Based Category-Level Object Pose Estimation via Depth Recovery and Adaptive Refinement

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IEEE robotics and Automation Letters 2025年第6期10卷 5377-5384页

作者： Yang, Hui Sun, Wei Liu, Jian Zheng, Jin Zeng, Zhiwen Mian, Ajmal Hunan University National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering Changsha410082 China Hunan University State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha410082 China Central South University School of Architecture and Art Changsha410082 China University of Western Australia Department of Computer Science and Software Engineering CrawleyWA6009 Australia

Category-level pose estimation methods have received widespread attention as they can be generalized to intra-class unseen objects. Although RGB-D-based category-level methods have made significant progress, reliance on depth image limits practical application. RGB-based methods offer a more practical and cost-effective solution. However, current RGB-based methods struggle with object geometry perception, leading to inaccurate pose estimation. We propose depth recovery and adaptive refinement for category-level object pose estimation from a single RGB image. We leverage DINOv2 to reconstruct the coarse scene-level depth from the input RGB image and propose an adaptive refinement network based on an encoder-decoder architecture to dynamically improve the predicted coarse depth and reduce its gap from the ground truth. We introduce a 2D–3D consistency loss to ensure correspondence between the point cloud obtained from depth projection and the objects in the 2D image. This consistency supervision enables the model to maintain alignment between the depth image and the point cloud. Finally, we extract features from the refined point cloud and feed them into two confidence-aware rotation regression branches and a translation and size prediction residual branch for end-to-end training. Decoupling the rotation matrix provides a more direct representation, which facilitates parameter optimization and gradient propagation. Extensive experiments on the REAL275 and CAMERA25 datasets demonstrate the superior performance of our method. Real-world estimation and robotic grasping experiments demonstrate our model robustness to occlusion, clutter environments, and low-textured objects. Our code and robotic grasping video are available at DA-Pose. © 2016 IEEE.

关键词： Depth perception

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CONCEPT OF THE advanced robot FOR NUCLEAR POWER PLANTS.

CONCEPT OF THE ADVANCED ROBOT FOR NUCLEAR POWER PLANTS.

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Proceedings of '85 International Conference on advanced robotics.

作者： Maki, H. Advanced Robot Technology Research Assoc Advanced Robot Technology Research Assoc

Regarding robots that are expected to play an important role when put into practical use at nuclear power plants in the 1990s, the concept of a targeted robot was established so as to efficiently develop a robot within a set period of time and budget by concentrating on the highest level of essential technology possible. This paper will mainly refer to the concept of the robot for nuclear power plants as well as various forms of essential technology currently spotlighted. The robot concept will be revised as necessary in accordance with the future progress of the essential technology.

关键词： robotS, INDUSTRIAL

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CONCEPT OF THE advanced robot FOR SUPPORT OF OFFSHORE OIL EXPLOITATION.

CONCEPT OF THE ADVANCED ROBOT FOR SUPPORT OF OFFSHORE OIL EX...

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Proceedings of '85 International Conference on advanced robotics.

作者： Tanaka, N. Advanced Robot Technology Research Assoc Advanced Robot Technology Research Assoc

We have time after time reexamined and refined the concept of advanced robot for support of offshore oil exploitation. In FY 1984, we carried out research and surveys centering on the current state of robotics technology for the purpose of ascertaining the boundaries and focus of research and development necessary for future R & D programs. In the present paper, we will comment mainly on the technologies of elements presently considered essential for the concept of an advanced robot for support of offshore oil exploitation.

关键词： robotS, INDUSTRIAL

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