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IEEE-RAS International Conference on Humanoid Robots

作者： Tobias Egle Yashuai Yan Dongheui Lee Christian Ott Automation and Control Institute TU Wien Vienna Austria Autonomous Systems Lab TU Wien Vienna Austria Institute of Robotics and Mechatronics (DLR) German Aerospace Center Wessling Germany

ISBN: (数字)9798350373578

ISBN: (纸本)9798350373585

This paper introduces a new approach to enhance the robustness of humanoid walking under strong perturbations, such as substantial pushes. Effective recovery from external disturbances requires bipedal robots to dynamically adjust their stepping strategies, including footstep positions and timing. Unlike most advanced walking controllers that restrict footstep locations to a predefined convex region, substantially limiting recoverable disturbances, our method leverages reinforcement learning to dynamically adjust the permissible footstep region, expanding it to a larger, effectively non-convex area and allowing cross-over stepping, which is crucial for counteracting large lateral pushes. Additionally, our method adapts footstep timing in real time to further extend the range of recoverable disturbances. Based on these adjustments, feasible footstep positions and DCM trajectory are planned by solving a QP. Finally, we employ a DCM controller and an inverse dynamics whole-body control framework to ensure the robot effectively follows the trajectory.

关键词： Legged locomotion Limiting Perturbation methods Humanoid robots Reinforcement learning Robustness Real-time systems Timing Trajectory IEEE Regions

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A Distributed Energy Sharing Framework for Communities with PV Prosumers and Aggregate EV Prosumers

A Distributed Energy Sharing Framework for Communities with ...

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Chinese Control and Decision Conference, CCDC

作者： Fan Chen Huaiyu Wu Mian Hu Yang Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Under the energy policy that encourages local consumption of renewable energy, energy sharing between neighboring prosumers is more effective compared with the case of independent operation of each prosumer. This paper proposes a new energy sharing framework of community prosumers, considering that the energy sharing operator (ESO) is equipped with two types of energy storage devices (batteries and powerto-gas devices) and the two types of prosumers (photovoltaic prosumers and aggregate electric vehicle prosumers) have both electricity and hydrogen loads. The Stackelberg game framework is designed with the ESO as leader and the two types of prosumers as followers. The ESO aims to maximize its revenue and coordinate the energy sharing between community prosumers by setting dynamic electricity prices. Each prosumer maximizes its payoff through optimal response. A distributed bi-level iterative algorithm is designed to solve the Stackelberg game equilibrium strategy, which can protect the privacy information of prosumers effectively. Simulation results are provided to show that the proposed community prosumer energy sharing framework can not only increase the benefits of the ESO and all prosumers, but also reduce the load pressure of the main grid.

关键词： Photovoltaic systems Privacy Renewable energy sources Electricity Simulation Aggregates Hydrogen

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Preparation and 3D printing of high-thermal-conductivity continuous mesophase-pitch-based carbon fiber/epoxy composites

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2023年第2期24卷 162-172页

作者： Haiguang ZHANG Kunlong ZHAO Qingxi HU Jinhe WANG Rapid Manufacturing Engineering Center School of Mechatronical Engineering and AutomationShanghai UniversityShanghai 200444China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai UniversityShanghai 200072China National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghai 200444China Nano-Science&Technology Research Center School of ScienceShanghai UniversityShanghai 200444China

To meet the requirements of spacecraft for the thermal conductivity of resins and solve the problem of low thermal conduction efficiency when 3D printing complex parts,we propose a new type of continuous mesophase-pitch-based carbon fiber/thermoplastic polyurethane/epoxy(CMPCF/TPU/epoxy)composite filament and its preparation process in this *** composite filament is based on the high thermal conductivity of CMPCF,the high elasticity of TPU,and the high-temperature resistance of *** tensile strength and thermal conductivity of the CMPCF/TPU/epoxy composite filament were *** CMPCF/TPU/epoxy composites are formed by 3D printing technology,and the composite filament is laid according to the direction of heat conduction so that the printed part can meet the needs of directional heat *** experimental results show that the thermal conductivity of the printed sample is 40.549 W/(m·K),which is 160 times that of pure epoxy resin(0.254 W/(m·K)).It is also approximately 13 times better than that of polyacrylonitrile carbon fiber/epoxy(PAN-CF/epoxy)*** study breaks through the technical bottleneck of poor printability of *** provides a new method for achieving directional thermal conductivity printing,which is important for the development of complex high-performance thermal conductivity products.

关键词： Thermal conductivity 3D printing Continuous mesophase-pitch-based carbon fiber(CMPCF) Thermoplastic polyurethane(TPU) Epoxy composite filament

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An End-to-End Proprioception Framework for Soft Continuum Robot

An End-to-End Proprioception Framework for Soft Continuum Ro...

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IEEE International Conference on robotics and Biomimetics

作者： Hanwen Cao Wei Chen Yiang Lu Junda Huang Jianshu Zhou Yunhui Liu Department of Mechanical and Automation Engineering The T Stone Robotics Institute The Chinese University of Hong Kong the Hong Kong Center for Logistics Robotics (HKCLR)

ISBN: (纸本)9781665481106

Soft robots are gaining more and more attention owing to their inherent compliance and excellent flexibility, enabling new potentials for robots to address real-world chal-lenges in the manner of their natural counterparts. The soft con-tinuum robot is one typical example that reflects the successful inspiration achievement from biomimetics to robotics. However, due to the nonlinearity and ultra-high degrees of freedom of soft continuum robots, traditional kinematic modeling methods obtain unsatisfying precision, especially when robots interact with their surroundings. To precisely estimate the kinematic model of soft continuum robots, we propose a novel end-to-end proprioception method. Our method inputs time series data from the soft continuum robot actuators and outputs the end-tip position in three dimensions. The experimental results show that the proposed method can improve the kinematic accuracy compared to the constant curvature model-based method either with contact or in noncontact conditions.

关键词： Actuators Biomimetics Biological system modeling Time series analysis Kinematics Soft robotics Robots

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A Hierarchical Energy Sharing Strategy for Multi-Communities with Heterogeneous Prosumers

A Hierarchical Energy Sharing Strategy for Multi-Communities...

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Chinese automation Congress (CAC)

作者： Yan Yang Fan Chen Mian Hu Huaiyu Wu Yang Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Inter-community energy sharing is of positive significance in the energy transacion market, which can effectively reduce the cost of purchasing energy from the utility grid and improve the local consumption of renewable energy. In this study, a hierarchical energy sharing framework for multi-communities with heterogeneous prosumers is proposed. Each community consists of different types of prosumers, that is, photovoltaic (PV) prosumers, wind turbine (WT) prosumers and aggregate electric vehicle (EV) prosumers. A hierarchical energy sharing strategy based on Stackelberg game is proposed. In the inner cooperation stage, the total cost minimization model of operator cluster is established. In the outer non-cooperative stage, the Stackelberg game model between each operator and heterogeneous prosumers in each community is established, and the robust optimization method is adopted to solve the time-varying uncertainty problem of renewable energy generations. A hierarchical iterative algorithm is designed to solve the Stackelberg game equilibrium strategy, which maximizes each prosumer's income and minimizes the operators' total cost. The simulation results show that the proposed multi-community hierarchical energy sharing strategy can not only reduce the impact of load fluctuation on the utility grid, but also improve the income of prosumers.

关键词： Photovoltaic systems Renewable energy sources Costs Fluctuations Uncertainty Simulation Games Minimization Wind turbines Iterative methods

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The Accuracy Analysis of Tool center Point Calibration via Condition Number and Minimum Eigenvalue

The Accuracy Analysis of Tool Center Point Calibration via C...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Ziqi Gao Yingli Li Yang Luo Yunxiang Jiang Bi Zhang Xingang Zhao Lingkai Chen Yiwen Zhao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Lab Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China

The accuracy of TCP (tool center point) calibration is vital to the operation accuracy of the robot. In this paper, we analyzed the accuracy analysis of TCP calibration of the regression matrix via condition number and minimum eigenvalue. It is theoretically proved that a regression matrix with a large condition number and a small eigenvalue will aggravate the influence of the observation error of the measurement point on TCP calibration accuracy and increase the TCP calibration error. To verify our analysis, simulation calibration experiments were carried out and statistical analysis was carried out on the calibration results. The result shows that the mathematical expectation and the variance of calibration error at minimum, median, and maximum matrix CA condition number are 1.36mm (±0.60mm), 1.57mm (± 0.75mm) and 2.94mm (±2.26mm) respectively, and the mathematical expectation and the variance of calibration error at minimum, median, and maximum eigenvalue are 3.33mm (± 2.32mm), 1.54mm (±0.72mm) and 1.16mm (± 0.49mm), respectively.

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Learning Representation for Clustering via Dual Correlation

Learning Representation for Clustering via Dual Correlation

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IEEE Information Technology, Networking, Electronic and automation Control Conference

作者： Tao Zhang Mingming Hu State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing University of Chinese Academy of Sciences Shenyang China Data Management Department Center for Clinical Studies Beijing China

Contrastive learning is a self-supervised learning method used to learn the general features of a dataset without labels by letting the model learn which data points are similar or different. It constructs labeled samples through data augmentation. Therefore, the core and difficulty of self-supervised contrastive learning are to construct high-quality contrastive samples, especially negative sample pairs. In this paper, a cluster-based contrast sample selection method is proposed, which selects the positive contrast samples from the same cluster and the negative contrast samples from different clusters. By minimizing the forward contrast sample loss and maximizing the reverse sample loss, the deep representation clustering result of the image is obtained. The experimental results show the excellence and adaptability of the algorithm.

关键词： Correlation automation Clustering algorithms Self-supervised learning Data models

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Category Theory for Autonomous Robots: The Marathon 2 Use Case

arXiv

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arXiv 2023年

作者： Aguado, Esther Gómez, Virgilio Hernando, Miguel Rossi, Claudio Sanz, Ricardo Universidad Politécnica de Madrid Autonomous Systems Laboratory Center for Automation and Robotics c/ José Gutierrez Abascal 2 Madrid28006 Spain

Model-based systems engineering (MBSE) is a methodology that exploits system representation during the entire system life-cycle. The use of formal models has gained momentum in robotics engineering over the past few years. Models play a crucial role in robot design;they serve as the basis for achieving holistic properties, such as functional reliability or adaptive resilience, and facilitate the automated production of modules. We propose the use of formal conceptualizations beyond the engineering phase, providing accurate models that can be leveraged at runtime. This paper explores the use of Category Theory, a mathematical framework for describing abstractions, as a formal language to produce such robot models. To showcase its practical application, we present a concrete example based on the Marathon 2 experiment. Here, we illustrate the potential of formalizing systems—including their recovery mechanisms—which allows engineers to design more trustworthy autonomous robots. This, in turn, enhances their dependability and performance. © 2023, CC BY.

关键词： Robots

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Zero-Shot Kidney Stone Segmentation Based on Segmentation Anything Model for Robotic-Assisted Endoscope Navigation 16th

Zero-Shot Kidney Stone Segmentation Based on Segmentation A...

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

作者： Meng, Hui Chen, Lingkai Zhu, Shiqiang Fei, Chentao Zhang, Yong Zheng, Miaojuan Han, Jianda Song, Wei School of Intelligent Science and Technology Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences 1 Sub-lane Xiangshan Hangzhou310024 China Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Hangzhou ElephantChain Network Technology Co. Ltd. Hangzhou China Faculty of Mechanical Engineering and Automation Zhejiang Sci-Tech University Hangzhou310018 China College of Artificial Intelligence and Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information Systems Nankai University Tianjin300350 China

ISBN: (纸本)9789819964888

Biomedical robotics has had a significant impact on flexible ureteroscopy (FURS) for the management of nephrolithiasis. The biomedical robots provide a suitable and safe platform for FURS. However, operating the robots expertly still represents a challenge for surgeons. Vision-based navigation is an effective means to simplify the operations of robots by surgeons, which has great potential to improve surgical efficiency. To achieve vision-based navigation, the localization of kidney stones in endoscopic images is the first step. In this paper, we propose a stone segmentation method (SSM) based on zero-shot learning, which consists of segmentation anything model (SAM), an image preprocessing module, and a mask postprocessing module. The SAM segments all objects in endoscopic images, which lack semantic information. The preprocessing module is designed to suppress interference of reflective area in endoscopic images, and the mask postprocessing module is used to filter noise masks. The experimental results on our collected endoscopic images indicate that our method achieves close accuracy on stone segmentation compared with supervised U-Net and VGG_U-Net, which significantly outperforms the Ostu and the SAM. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Endoscopy

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Diffusion Trajectory-guided Policy for Long-horizon Robot Manipulation

arXiv

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arXiv 2025年

作者： Fan, Shichao Yang, Quantao Liu, Yajie Wu, Kun Che, Zhengping Liu, Qingjie Wan, Min School of Mechanical Engineering and Automation BeiHang University China School of Computer Science and Engineering BeiHang University China Beijing Innovation Center of Humanoid Robotics China KTH Royal Institute of Technology Sweden

Recently, Vision-Language-Action models (VLA) have advanced robot imitation learning, but high data collection costs and limited demonstrations hinder generalization and current imitation learning methods struggle in out-of-distribution scenarios, especially for long-horizon tasks. A key challenge is how to mitigate compounding errors in imitation learning, which lead to cascading failures over extended trajectories. To address these challenges, we propose the Diffusion Trajectory-guided Policy (DTP) framework, which generates 2D trajectories through a diffusion model to guide policy learning for long-horizon tasks. By leveraging task-relevant trajectories, DTP provides trajectory-level guidance to reduce error accumulation. Our two-stage approach first trains a generative vision-language model to create diffusion-based trajectories, then refines the imitation policy using them. Experiments on the CALVIN benchmark show that DTP outperforms state-of-the-art baselines by 25% in success rate, starting from scratch without external pretraining. Moreover, DTP significantly improves real-world robot performance. All source code and experiment videos will be released upon acceptance. Copyright © 2025, The Authors. All rights reserved.

关键词： Visual languages

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