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IEEE International Conference on robotics and automation (ICRA)

作者： Hanjing Ye Jieting Zhao Yaling Pan Weinan Cherr Li He Hong Zhang Department of Electronic and Electrical Engineering Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology (SUSTech) SUSTech Biomimetic and Intelligent Robotics Lab Guangdong University of Technology

Robot person following (RPF) is a capability that supports many useful human-robot-interaction (HRI) applications. However, existing solutions to person following often as-sume full observation of the tracked person. As a consequence, they cannot track the person reliably under partial occlusion where the assumption of full observation is not satisfied. In this paper, we focus on the problem of robot person following under partial occlusion caused by a limited field of view of a monocular camera. Based on the key insight that it is possible to locate the target person when one or more of hislher joints are visible, we propose a method in which each visible joint contributes a location estimate of the followed person. Experiments on a public person-following dataset show that, even under partial occlusion, the proposed method can still locate the person more reliably than the existing SOTA methods. As well, the application of our method is demonstrated in real experiments on a mobile robot.

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Multi-Scale Point Octree Encoding Network for Point Cloud Based Place Recognition

Multi-Scale Point Octree Encoding Network for Point Cloud Ba...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Zhilong Tang Hanjing Ye Hong Zhang Department of Electrical and Electronic Engineering Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology (SUSTech) SUSTech Shenzhen China

Over the past decades, point cloud-based place recognition has garnered significant attention. This research paper presents a pioneering approach, denoted as the Multi-scale Point Octree Encoding Network (MPOE-Net), designed to acquire a discriminative global descriptor for efficient retrieval of places. The key element of the MPOE-Net is the point octree encoding module, which adeptly captures local information for each point by considering its nearest and farthest neighbors. Further enhancing local relationships, a multi-transformer network is introduced, utilizing a novel grouped offset-attention mechanism. To amalgamate the multi-scale attention maps into a comprehensive global descriptor, a multi-NetVLAD layer is incorporated. Through rigorous experimentation across diverse benchmark datasets, our proposed method unequivocally outperforms existing techniques in the realm of point cloud-based place recognition tasks, achieving state-of-the-art results. Our code is released publicly at https://***/Zhilong-Tang/MPOE-Net.

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Enhancing Precision Agriculture Through Human-in-the-Loop Planning and Control

Enhancing Precision Agriculture Through Human-in-the-Loop Pl...

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IEEE International Conference on automation Science and engineering (CASE)

作者： Shankar A. Deka Sujet Phodapol Andreu Matoses Gimenez Victor Nan Fernandez-Ayala Rufus Wong Pian Yu Xiao Tan Dimos V. Dimarogonas Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Division of Decision and Control Systems School of EECS Royal Institute of Technology (KTH) Stockholm Sweden Department of Cognitive Robotics Faculty of Mechanical Engineering TU Delft Delft Netherlands Department of Computer Science University of Oxford Oxford UK

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we introduce a ROS based framework designed for the planning and control of robotic systems within the context of precision agriculture, with an emphasis on human-in-the-loop capabilities. Utilizing Linear Temporal Logic to articulate complex task specifications, our algorithm creates high-level robotic plans that are not only correct by design but also adaptable in real time by human operators. This dual-focus approach ensures that while humans have the flexibility to modify the high-level plan on-the-fly or even take over low-level control of the robots, the system inherently safeguards against any human actions that could potentially breach the predefined task specifications. We demonstrate our algorithm within the dynamic and challenging environment of a real vineyard, where the collaboration between human workers and robots is critical for tasks such as harvesting and pruning, and show the practical applicability and robustness of our software. This work marks a pioneering application of formal methods to complex, real-world agricultural environments.

关键词： Precision agriculture Heuristic algorithms Software algorithms Robustness Human in the loop Software Real-time systems Planning Robots Multi-agent systems

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Longitudinal velocity control of autonomous driving based on extended state observer

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CAAI Transactions on Intelligence Technology 2025年第1期10卷 36-46页

作者： Hongbo Gao Hanqing Yang Xiaoyu Zhang Xiangyun Ren Fenghua Liang Ruidong Yan Qingchao Liu Mingmao Hu Fang Zhang Jiabing Gao Siyu Bao Keqiang Li Deyi Li Danwei Wang Department of Automation University of Science and Technology of ChinaHefeiChina State Key Laboratory of Intelligent Vehicle Safety Technology ChongqingChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Traffic and Transportation Beijing Jiaotong UniversityBeijingChina Automotive Engineering Research Institute Jiangsu UniversityZhenjiangChina School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingaporeSingapore School of Automotive Engineering Hubei University of Automotive TechnologyShiyanChina Beijing Idriverplus Technology Co. Ltd.BeijingChina Chery Automobile Co. Ltd.WuhuChina State Key Laboratory of Automotive Safety and Energy Tsinghua UniversityBeijingChina Department of Computer Science and Technology Tsinghua UniversityBeijingChina

Active Disturbance Rejection Control(ADRC)possesses robust disturbance rejection capabilities,making it well-suited for longitudinal velocity ***,the conventional Extended State Observer(ESO)in ADRC fails to fully exploit feedback from first-order and higher-order estimation errors and tracking error simultaneously,thereby diminishing the control performance of *** address this limitation,an enhanced car-following algorithm utilising ADRC is proposed,which integrates the improved ESO with a feedback *** comparison to the conventional ESO,the enhanced version effectively utilises multi-order estimation and tracking ***,it enhances convergence rates by incorporating feedback from higher-order estimation errors and ensures the estimated value converges to the reference value by utilising tracking error *** improved ESO significantly enhances the disturbance rejection performance of ***,the effectiveness of the proposed algorithm is validated through the Lyapunov approach and experiments.

关键词： active disturbance rejection control(ADRC) autonomous vehicle extended state observer(ESO) intelligent control longitudinal velocity control

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Cooperative Output Regulation of Multi-Agent Systems under Distributed Denial of Service Attacks

Cooperative Output Regulation of Multi-Agent Systems under D...

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第42届中国控制会议

作者： GAO Weinan JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Department of Electrical and Computer Engineering Tandon School of Engineering New York University

This paper aims to tackle the cooperative output regulation problem of multi-agent systems with the existence of distributed denial of service attacks. The proposed solution consists of two steps. First, develop a distributed control policy with internal models, and then analyze the resilience of closed-loop systems. Through the notion of input-to-state stability and Lyapunov stability theory, a bound of distributed denial of service duration is obtained under which the closed-loop systems achieve cooperative output regulation. The efficiency is validated by numeric simulations.

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LP-ICP: General Localizability-Aware Point Cloud Registration for Robust Localization in Extreme Unstructured Environments

arXiv

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arXiv 2025年

作者： Yue, Haosong Xu, Qingyuan Chen, Fei Pan, Jia Chen, Weihai School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Hong Kong Department of Computer Science The University of Hong Kong Hong Kong Hangzhou Innovation Institute Beihang University Hangzhou310053 China

The Iterative Closest Point (ICP) algorithm is a crucial component of LiDAR-based SLAM algorithms. However, its performance can be negatively affected in unstructured environments that lack features and geometric structures, leading to low accuracy and poor robustness in localization and mapping. It is known that degeneracy caused by the lack of geometric constraints can lead to errors in 6-DOF pose estimation along ill-conditioned directions. Therefore, there is a need for a broader and more fine-grained degeneracy detection and handling method. This paper proposes a new point cloud registration framework, LP-ICP, that combines point-to-line and point-to-plane distance metrics in the ICP algorithm, with localizability detection and handling. LP-ICP consists of a localizability detection module and an optimization module. The localizability detection module performs localizability analysis by utilizing the correspondences between edge points (with low local smoothness) to lines and planar points (with high local smoothness) to planes between the scan and the map. The localizability contribution of individual correspondence constraints can be applied to a broader range. The optimization module adds additional soft and hard constraints to the optimization equations based on the localizability category. This allows the pose to be constrained along ill-conditioned directions, with updates either tending towards the constraint value or leaving the initial estimate unchanged. This improves accuracy and reduces fluctuations. The proposed method is extensively evaluated through experiments on both simulation and real-world datasets, demonstrating higher or comparable accuracy than the state-of-the-art methods. The dataset and code of this paper will also be open-sourced at https://***/xuqingyuan2000/LP-ICP. Copyright © 2025, The Authors. All rights reserved.

关键词： Constrained optimization

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Robots Taking Initiative in Collaborative Object Manipulation: Lessons from Physical Human-Human Interaction

arXiv

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arXiv 2023年

作者： Rysbek, Zhanibek Oh, Ki Hwan Shervedani, Afagh Mehri Klemenčič, Timotej Žefran, Miloš Di Eugenio, Barbara Robotics Lab Department of Electrical and Computer Engineering The University of Illinois at Chicago ChicagoIL60607 United States Laboratory of Robotics Faculty of Electrical Engineering University of Ljubljana Slovenia Natural Language Processing Lab Department of Computer Science The University of Illinois at Chicago ChicagoIL60607 United States

Physical Human-Human Interaction (pHHI) involves the use of multiple sensory modalities. Studies of communication through spoken utterances and gestures are well established, but communication through force signals is not well understood. In this paper, we focus on investigating the mechanisms employed by humans during the negotiation through force signals, and how the robot can communicate task goals, comprehend human intent, and take the lead as needed. To achieve this, we formulate a task that requires active force communication and propose a taxonomy that extends existing literature. Also, we conducted a study to observe how humans behave during collaborative manipulation tasks. An important contribution of this work is the novel features based on force-kinematic signals that demonstrate predictive power to recognize symbolic human intent. Further, we show the feasibility of developing a real-time intent classifier based on the novel features and speculate the role it plays in high-level robot controllers for physical Human-Robot Interaction (pHRI). This work provides important steps to achieve more human-like fluid interaction in physical co-manipulation tasks that are applicable and not limited to humanoid, assistive robots, and human-in-the-loop automation. Copyright © 2023, The Authors. All rights reserved.

关键词： Human robot interaction

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Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 985-996页

作者： Lei Zou Zidong Wang Bo Shen Hongli Dong Guoping Lu College of Information Science and Technology Donghua UniversityShanghai 201620 Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Brunel University LondonUxbridgeMiddlesex UB83PHUK Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying *** to the inherent vulnerability of network-based communication,the measurement signals transmitted over a communication network might be intercepted by potential *** avoid information leakage,by resorting to an artificial-noise-assisted method,we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term.A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption *** purpose of the addressed problem is to design an encryptiondecryption scheme and a state estimator such that:1)the desired secrecy capacity is ensured;and 2)the required finite-horizon–l_(2)-l_(∞)performance is *** conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state ***,simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.

关键词： Artificial-noise-assisted technique eavesdropping encryption-decryption scheme energy-to-peak state estimation finitehorizon state estimation

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Design and Application of a One-Stop Mobile Application Sharing Platform for Steel Enterprises 42

Design and Application of a One-Stop Mobile Application Shar...

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42nd Chinese Control Conference, CCC 2023

作者： Chen, Xinzhe Chen, Luefeng Hu, Jie Yang, Qingfeng Wu, Min Pedrycz, Witold School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada

ISBN: (纸本)9789887581543

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance. © 2023 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Informatization

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Human Multi-dimensional Stiffness Skills Transfer for Robot Teleoperation System

Human Multi-dimensional Stiffness Skills Transfer for Robot ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Liwen Situ Zhenyu Lu Weiyong Si Chenguang Yang College of Automation Science and Engineering South China University of Technology Guangzhou China Bristol Robotics Laboratory University of the West of England Bristol UK Department of Computer Science University of Liverpool Liverpool UK

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Neuroscience research has demonstrated the sig-nificance of modulating stiffness during human task performance. Similarly, endowing robots with such capability is expected. However, existing methods for robot teleoperation require operators to simultaneously control position and stiffness, resulting in high workload and task inefficiency. On the other hand, learning from demonstration (LfD) offers a feasible approach for autonomously generating stiffness. Therefore, this paper proposes a robot teleoperation system that combines the advantages of teleoperation and LfD. Teleoperation enables precise positioning guided by human operators, while LfD can transfer human stiffness skills to robots. A teleoperation-oriented stiffness-adaptive Gaussian Mixture Model/Gaussian Mixture Regression method is proposed to learn human multi-dimensional stiffness and reproduce robot stiffness on a Riemannian manifold. To enhance generalization and cooperate with teleoperation, reference points and position-driven output are introduced. Furthermore, a teleoperation strategy for both the single-leader-single-follower configuration and the single-leader-dual-follower configuration are designed, which allows operators to control either one or two robot arms with a single leader device. Finally, the effectiveness of our method is verified through a plugging-in task and a continuous flipping task, demonstrating that the proposed system is capable of performing tasks that demand high positioning accuracy and stiffness adjustment. A supplementary video for this paper is available in GitHub**https://***/setowenGit/TOSA-GMM-GMR-Video.

关键词： Manifolds Performance evaluation Hands Accuracy Neuroscience Sockets Manipulators Robots Cybernetics

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