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IEEE Transactions on intelligent Vehicles 2024年 1-13页

作者： Gao, Jianqi Li, Yanjie Ye, Zhaohui Wu, Xinyu Department of Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics and School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

Multi-agent path finding (MAPF) is an essential issue for warehouse automation, where multiple agents plan collision-free paths from the start to goal positions. Reinforcement learning (RL) has been employed to develop partially observable distributed MAPF methods that can be scaled to any number of agents. However, existing RL-based MAPF methods still have some limitations in handling redundant information and avoiding deadlock, resulting in a low success rate or longer makespan. This paper proposes a Priority-aware Communication & Experience learning method (PCE), which combines RL with a novel priority-aware multi-agent communication and a new priority-aware deadlock experience replay to tackle this challenge. To be specific, our innovation encompasses two-fold. Our proposed communication mechanism aims to handle redundant information, which establishes a dynamic communication topology based on agents' priorities and proposes a two-head priority-aware graph attention network to aggregate information. In order to help the agent avoid deadlock, we prioritize the expert experience that solves the deadlock when performing experience replay. We conduct multiple simulation experiments on warehouse-like structured grid maps. Compared with the state-of-the-art RL-based MAPF methods, PCE performs significantly better with a higher success rate and lower makespan in small and large MAPF and higher average throughput in the lifelong MAPF, which can further improve the efficiency of warehouse automation. Finally, we validate PCE using three Turtlebot3-Burger robots, which shows that PCE can be applied in real warehouse automation scenarios. IEEE

关键词： Aggregates

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Learning Agile Quadrotor Flight in Restricted Environments with Safety Guarantees

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年第9期9卷 1-8页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Wu, Xinyu Department of Control Science and Engineering Harbin Institute of Technology Shenzhen and Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. This paper focuses on the safety issue of Reinforcement Learning (RL)-based control for agile quadrotor flight in restricted environments. To this end, we propose a unified Adaptive Safety Predictive Corrector (ASPC) to certify each output action of the RL-based controller in real-time, ensuring its safety while maintaining agility. Specifically, we develop the ASPC as a finite-horizon optimal control problem, formulated by a variant of Model Predictive Control (MPC). Given the safety constraints determined by the restricted environment, the objective of minimizing loss of agility can be optimized by reducing the difference between the actions of RL and ASPC. As the safety constraints are decoupled from the RL-based control policy, the ASPC is plug-and-play and can be incorporated into any potentially unsafe controllers. Furthermore, an online adaptive regulator is presented to adjust the safety bounds of the state constraints with respect to the environment changes, extending the proposed ASPC to different restricted environments. Finally, simulations and real-world experiments are demonstrated in various restricted environments to validate the effectiveness of the proposed ASPC. IEEE

关键词： Reinforcement learning

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FWAF-VID: A Flapping-Wing Aggressive Flight Benchmark Dataset for Visual-Inertial Localization

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IEEE robotics and Automation Letters 2025年第6期10卷 6328-6335页

作者： Jiang, Jizhou Pan, Erzhen Xu, Wenfu Sun, Wei Ye, Jingyang Harbin Institute of Technology School of Robotics and Advanced Manufacture Shenzhen518055 China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China Guangdong Biomimetic Intelligent Unmanned System Engineering Technology Research Center Shenzhen518052 China

Accurate state estimation of micro aerial vehicles (MAVs) in high-speed and dynamic environments poses a significant challenge for visual-inertial odometry (VIO) algorithms. Flapping-wing aerial vehicles (FWAVs), as an emerging flight platform, have attracted significant attention for stealth capabilities and efficient flight characteristics. Despite the availability of numerous MAV visual-inertial datasets for six-degree-of-freedom (6-DoF) state estimation, these datasets are not applicable for FWAVs with pronounced vibrations and agile maneuverability. To address this gap, we propose a large-scale flapping-wing aggressive flight visual-inertial dataset FWAF-VID. It contains diverse integrations of synchronized onboard cameras and IMU sensors. A total of 28 sequences include static flapping, calibration, and real-world flights collected in outdoor and indoor environments. The 17 flight sequences feature variations in illuminations, speeds, trajectories, camera perspectives, and flight modalities. We provide precisely aligned ground truth RTK and UWB measurements for algorithm evaluation. Furthermore, a comprehensive benchmark comparison is conducted, qualitatively and quantitatively evaluating the positioning accuracy of state-of-the-art VIO algorithms. The experimental results indicate that despite the degradation in localization accuracy in high-dynamic environments, FWAF-VID can effectively support the further development of VIO algorithms for FWAVs. To the best of our knowledge, this is the first onboard benchmark dataset tailored for aggressive flight in flapping-wing airborne platforms. © 2025 IEEE.

关键词： Micro air vehicle (MAV)

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TrinityMag:A novel magnetically actuated miniature robot manipulating system with a human-scale workspace

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Science China(Technological Sciences) 2024年第11期67卷 3546-3558页

作者： LI Dong CHEN BinHan HUANG ChenYang XU Sheng WU XinYu XU TianTian Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Key Laboratory of Biomedical Imaging Science and System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China

The development of the magnetic manipulating system is essential for applications of magnetically actuated miniature robots in biomedical practice,such as targeted therapy and precise ***,the workspaces of existing magnetic manipulating systems for miniature robots are mostly insufficient to manipulate miniature robots inside human *** present study proposes an innovative electromagnets-based manipulating system,TrinityMag,which can produce dynamic three-dimensional(3D)magnetic fields in a human-scale spherical workspace with a 2.6 m *** magnetic field of a single electromagnet is simulated,and a new calibration technic is designed based on deep learning ***,the arrangement of three electromagnets is optimized to produce maximal 3D arbitrary magnetic fields with limited ***,a target-tracking algorithm is developed so that the TrinityMag can track the miniature robot in real ***,the TrinityMag is validated in experiments to manipulate a soft millirobot to move in human-scale tortuous tracks with two types of *** maximum speed of the soft millirobot reaches 11.05 body length/*** work contributes to a significant increment in the workspace of the electromagnets-based manipulating system for miniature *** further expect that the TrinityMag could push the applications of miniature robots from laboratory to clinical practice.

关键词： magnetic manipulating system human-scale workspace magnetically actuated miniature robots

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Obstacle avoidance in human-robot cooperative transportation with force constraint

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Science China(Information Sciences) 2023年第1期66卷 334-335页

作者： Ying ZHANG Chenguang YANG Sheng XU Yongsheng OU College of Automation Science and Engineering South China University of Technology Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences

Dear editor,Robots are often conceived as human-like machines that can interact with humans naturally and safely. Human-robot interaction means that robots can communicate with people,understand their needs, and act accordingly [1]. This interaction is critical when two people are needed to finish a task cooperatively.

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Electric Vehicle Routing Problem with Capacitated Charging Stations and Dynamic Electricity Prices

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IEEE Internet of Things Journal 2025年第13期12卷 23763-23772页

作者： He, Zhiye Tian, Yuning Miao, Haoyu Yao, Canqi Yang, Zaiyue Shenzhen Key Laboratory of Control Theory and Intelligent Systems Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities School of System Design and Intelligent Manufacturing Shenzhen518055 China The Hong Kong Polytechnic University Department of Logistics and Maritime Studies Hong Kong Hong Kong

With rapid electrification of transportation systems in recent years, the electric vehicle routing problem (EVRP) has received increasing attention. In order to serve a set of valuable transportation tasks using a fleet of electric vehicles, EVRP intends to jointly determine their routes and the charging schedules, with the aim of optimizing service reward and charging cost under state of charge (SOC) constraints of battery. EVRP is a difficult nonlinear integer program, and due to its intrinsic NP-hardness early EVRP studies often oversimplify the charging process and assume unlimited capacity of charging stations and constant electricity price. The contribution of this paper lies in twofold. First, to better characterize the practical charging process, this paper introduces a new graph model that can take the charging station capacity and dynamic electricity price into full consideration. Second, we design a series of transformation techniques, including reformulation SOC dynamics, Lagrangian relaxation, exact linear programming relaxation, etc, which eventually convert the original EVRP into an approximate linear program. Extensive simulations across 14 instances demonstrate that, the proposed approach is capable of solving large-scale instances over 500 nodes, and is 100 times faster than traditional analytic methods while achieving very close optimality. While comparing with the popular heuristic method ALNS (Adaptive Large Neighborhood Search), our method is several times faster and obtains much better optimality. © 2014 IEEE.

关键词： Charging stations

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General Kinetostatic Modeling and Deformation Analysis of a Two-Module Rod-Driven Continuum Robot with Friction Considered

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Chinese Journal of Mechanical Engineering 2023年第3期36卷 110-122页

作者： Peiyi Wang Xinhua Yang Xiangyang Wang Sheng Guo School of Mechanical Electronic and Control EngineeringBeijing Jiaotong UniversityBeijing 100044China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518005China

Continuum robots actuated by flexible rods have large potential applications,such as detection and operation tasks in confined environments,since the push and pull actuation of flexible rods withstand tension and compressive force,and increase the structure's *** this paper,a generalized kinetostatics model for multi-module and multi-segment continuum robots considering the effect of friction based on the Cosserat rod theory is ***,the model is applied to a two-module rod-driven continuum robot with winding ropes to analyze its deformation and load *** different in-plane configurations under the external load term as S1,S2,C1,and C2 are *** a bending plane as an example,the tip deformation along thex-axis of these shapes is simulated and compared,which shows that the load capacity of C1 and C2 is generally larger than that of S1 and ***,the deformation experiments and simulations show that the maximum error ratio without external loads relative to the total length is no more than 3%,and it is no more than 4.7%under the external *** established kinetostatics model is proven sufficient to accurately analyze the rod-driven continuum robot with the consideration of internal friction.

关键词： Rod-driven continuum robot Kinetostatic model Cosserat rod theory Deformation and stiffness analysis

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Pressure Pain Recognition for Lower Limb Exoskeleton Robot with Physiological Signals 1

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2nd International Conference on Cognitive Computation and systems, ICCCS 2023

作者： Ma, Yue Wu, Xinyu Wang, Xiangyang Li, Jinke Qin, Pengjie Yin, Meng Cao, Wujing Yi, Zhengkun Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China SIAT-CUHK Joint Laboratory of Robotics and Intelligent Systems Guangdong Shenzhen China Shandong Institute of Advanced Technology Chinese Academy of Sciences Shandong Jining China

ISBN: (数字)9789819708857

ISBN: (纸本)9789819708840

Pain is a feedback mechanism the body uses to protect itself. The perception of human pain is still missing in lower limb exoskeleton robots, such as the pain caused by the pressure between the knee joint and the baffle when the lower limb exoskeleton stands up, or the pain caused by the mismatch between the gait and the body function of the wearer when walking. Aiming at the pain perception problem of the exoskeleton robot, this study designed a pressure pain data acquisition paradigm combined first considering the movement mode of the exoskeleton robot, and collected facial electromyography and electrocardiography signals, as well as five levels of pain. Then a deep learning neural Network based on Temporal Convolutional Network and Long Short-Term Memory is designed. The composite Loss of Center Loss, InfoNEC Loss and Softmax Loss is designed. The designed deep neural network model was evaluated using the thermal pain dataset BioVid, and the average recognition rate using only electrocardiography signals reached 86.44%. By Using the fusion signals of electrocardiography, electrocardiogram and electromyogram signals, the average recognition accuracy can reach 87.16%, which is superior to other similar methods, and verifies the effectiveness of the proposed method. The proposed network is also used to verify the collected pressure pain dataset, and the recognition accuracy can reach 87.5%, which proves the validity of the collected data set. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Electrocardiography

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Gait recognition based on sEMG and Deep Residual Shrinkage Network

Gait recognition based on sEMG and Deep Residual Shrinkage N...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Luo, Mingxiang Yang, Lijun Sun, Zeyu Yin, Meng Ma, Yue Wu, Xinyu Cao, Wujing Chinese Academy of Sciences and Southern University of Science and Technology Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology China Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518005 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch China University of Birmingham United Kingdom

ISBN: (纸本)9798350327182

Transverse resistance exoskeleton is expected to provide better rehabilitation training methods for patients with lower limb injury. Lateral walking gait recognition plays an important role in lateral resistance exoskeleton control. In the phase of lateral walking out of synchrony, the EMG signals produced by the thighs will be different. The EMG signals collected by five subjects while walking laterally were used in the experiment. The four muscles are: the gluteus medius of the left leg, the tensor fascia lata, the adductor major, and the tensor fascia lata of the right leg. Based on the one-dimensional EMG signals of the four muscles, this paper uses the classification model commonly used in the MATlab toolbox for training and recognition. However, the experimental results show that TREE and KNN have poor recognition accuracy for the four gait stages. To this end, this paper applies the convolutional residual shrinkage network (DRSN) to this occasion. The collected one-dimensional EMG signals are plotted as pictures and fed into the model for training and classification. Experimental results show that the classification accuracy is greatly improved compared with the previous model. © 2023 IEEE.

关键词： Muscle

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Optimization of a Piezoelectric Bending Beam-based Human Knee Energy Harvester 20

Optimization of a Piezoelectric Bending Beam-based Human Kne...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Liao, Haisu Wang, Yidi Shi, Qiuyu Huang, Ruisen Gao, Fei Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy System

ISBN: (纸本)9798350320831

The concept of extracting energy from the human body to recharge depleted energy sources has gained significant attention. Recently, scientists have focused on harnessing biomechanical energy from the human body while walking. The aim of this study is to optimize a piezoelectric bending beam-based human knee energy harvester to enhance performance. Specifically, the shape of the bending beam (the substrate: a carbon fiber plate) is optimized to modulate the deformation, such that the average strain of the piezoelectric macro fiber composites (MFC) attached to the bending beam is improved to generate more electricity. In addition, the effects of the substrate's thickness and the hinge base's height for the bending beam on the output power are also analyzed. Experimental testing on a subject is conducted to validate our design and test the performance. The harvester generates an average power output of 24.55 mW when walking at 4 km/h on a treadmill. The harvester's total weight is 278g. © 2023 IEEE.

关键词： Energy harvesting

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