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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Chen, Lin Wang, Yaonan Miao, Zhiqiang Mo, Yang Feng, Mingtao Zhou, Zhen School of Electrical and Information Engineering Hunan University Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Technology Changsha410082 China School of Computer Science and Technology Xidian University Xian710126 China

ISBN: (纸本)9781665481090

Multi-Agent Path Finding is a problem of finding the optimal set of paths for multiple agents from the starting position to the goal without conflict, which is essential to large-scale robotic systems. Imitation and reinforcement learning are applied to solve the MAPF problem and have achieved certain results, which provides a feasible solution for the path planning problem of large-scale robot systems. The current method improves the performance of distributed strategy-guided agent planning paths in complex environments by introducing the communication between graph neural networks and agents but dramatically reduces the system's robustness. This paper develops a novel imitation reinforcement learning framework by introducing Transformer, which enables algorithms to perform well in complex environments without relying on communication between agents. Compared with its counterparts, experiments show that the policy trained by our method guides the agent to drive from the initial position to the goal without collision and achieve better performance. © 2022 IEEE.

关键词： Reinforcement learning

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Safety-Critical control of Quadrotor UAVs with control Barrier Functions

Safety-Critical Control of Quadrotor UAVs with Control Barri...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Yang, Tianyi Miao, Zhiqiang Yi, Guo Wang, Yaonan College of Electrical and Information Engineering Hunan University Changsha410082 China National Engineering Research Center of Robot Visual Perception and Control Changsha China School of Information and Electrical Engineering Hunan University of Science and Technology Changsha411201 China

ISBN: (纸本)9781665481090

For quadrotors, imposing multiple dynamic constraints on the state simultaneously to achieve safe control is a challenging problem. In this paper, a cascaded control archi-tecture based on quadratic programming method is proposed to generate minimally-invasive and collision-free control actions. This architecture consists of exponential control barrier functions(ECBFs) to construct a non-conservative forward invariant safety region and geometric nonlinear PID attitude control with considering quadrotor dynamics to avoid the singularities of Euler-angles and the ambiguity of quaternions. The feasibility and the effectiveness of the proposed cascaded control architecture is demonstrated through numerical simulations. © 2022 IEEE.

关键词： Attitude control

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A Graph-Based SLAM Method Assisted by visual Marker in the Degenerate Scenes 8

A Graph-Based SLAM Method Assisted by Visual Marker in the D...

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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Zhang, Jieqingxin Zhang, Hui Zhou, Xidong Chen, Bo Wang, Xiangchuan Xu, Tao College of Electrical and Information Engineering Changsha University of Science and Technology Hunan China College of Robotics Robot Visual Perception and Control Technology National Engineering Research Center Hunan University Hunan China College of Electrical and Information Engineering Hunan University Hunan China

ISBN: (纸本)9798350300178

In the post-COVID-19 pandemic era, hospitals and other places have an urgent need for mobile robots with autonomous disinfection ability, and robots need to complete SLAM tasks to realize autonomous navigation. Lidar is widely used for indoor SLAM. However, due to the lack of geometric structure in the indoor environment, two-dimensional lidar information degrades, rendering the robot unable to obtain effective positioning. Therefore, we leverage the easy identification and high robustness of ARTag to fuse vision and range sensor information. We introduce ARTag as visual marker to assist positioning, establish observation window to screen the acquired ARTag pose. We employ the pose graph optimization method to optimize the visual markers and laser scanning results in the back end. This reduces the positioning errors caused by the degradation of lidar information and reduces the frequency of optimization by improving the back end optimization strategy. This method is applied in a UltraViolet C (UVC) Disinfection robot experiment. Experimental results show that our method effectively improves the positioning accuracy and robustness of the robot in the environments with degraded laser information. © 2023 IEEE.

关键词： Disinfection

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Geometric-based Bimodal control for Hybrid Aerial/Ground Vehicles

Geometric-based Bimodal Control for Hybrid Aerial/Ground Veh...

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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Tang, Haoming Miao, Zhiqiang Wang, Haoyu Chen, Yizong Zhang, Hui Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China National Engineering Research Center for Robot Visual Perception and Control Changsha China School of Robotics Hunan University Changsha410082 China

ISBN: (纸本)9798350372601

Hybrid ground/aerial vehicles, capable of adapting to both terrestrial and aerial environments simultaneously, can accomplish more complex tasks, holding promising applications across various domains. Furthermore, designing a highly real-time multi-modal controller to adapt to environmental and modal changes, is currently a critical issue to be addressed. Based on this requirement, a geometric-based bimodal control structure is proposed in this study. We initially design the aerial controller in the Lie algebra space, based on a geometric attitude controller. Moreover, inspired by the characteristics of ground locomotion, we modify the aerial controller to satisfy the constraints of this mode. Through this approach, we can simplify the design process of the ground controller. Both controllers feature a similar and simpler structure, meet real-time control requirements, and allow them to use the same parameters. Ultimately, the proposed method's efficacy and performance are validated through ROS-Gazebo simulation environment. © 2024 IEEE.

关键词： Antenna grounds

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Semi-supervised Cloud Edge Collaborative Power Transmission Line Insulator Anomaly Detection Framework 11th

Semi-supervised Cloud Edge Collaborative Power Transmission ...

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11th International Conference on Image and Graphics, ICIG 2021

作者： Yang, Yanqing Mao, Jianxu Zhang, Hui Chen, Yurong Zhong, Hang Huang, Zhihong Wang, Yaonan National Engineering Laboratory of Robot Visual Perception and Control Technology Hunan University Hunan Changsha China State Grid Hunan Electric Power Corporation Limited Research Institute Hunan Changsha China

ISBN: (纸本)9783030873547

The widely deployed power transmission line expedites developing the age of electricity. Thus, it is necessary to maintain a power system with a great quantity of manpower and material resources, especially for crucial equipment, such as insulator string. However, the current main inspection method relies on artificial with the problem of time-consuming and labor-intensive. There is a trend of utilizing deep learning techniques on unmanned aerial vehicles (UAVs) to accomplish the inspection task, but its development is restricted by the limitation of energy. In this paper, we propose a semi-supervised cloud edge collaborative insulator string anomaly detection framework. Specifically, an anchor-free object detector is deployed on the edge device for locating the insulator. On the cloud side, we propose a generative insulator defect detection model based on the autoencoder (AE) with a generator-discriminator pattern. Particularly, we introduce the variational memory encoder-decoder architecture to model defect-free insulator data distribution. Furthermore, the adversarial strategy is employed to regularize the generated data space with input data space. In the end, the anomaly can be detected if its data space is an outlier of training defect-free distribution. Comprehensive experiments demonstrate that our method can effectively reduce the computational load, meanwhile archiving superior performance, including accuracy (0.968) and recall (0.985), for defect recognition using a standard insulator data set. © 2021, Springer Nature Switzerland AG.

关键词： Deep learning

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Efficient Real-Time Recognition Model of Plant Diseases for Low-Power Consumption Platform

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2040-2054页

作者： Deng, Songyun Wu, Wanneng Zou, Kunlin Qin, Hai Cheng, Lekai Liang, Qiaokang Hunan University College of Electrical and Information Engineering Changsha410082 China Changsha University of Science and Technology School of Electrical and Information Engineering Changsha410114 China Hunan University National Engineering Research Center for Robot Vision Perception and Control College of Electrical and Information Engineering Changsha410082 China

Recognition and early warning of plant diseases is one of the keys to agricultural disaster prevention and mitigation. Deep learning-based image recognition methods give us a new idea for plant disease identification. Due to the harsh conditions in agricultural environment, recent research has focused on exploring ways to lightweight the recognition model for deployment on low-power devices. In this article, we propose an efficient and feature-guided real-time plant disease recognition model with a multiclassifier architecture, specifically designed for low-power devices. By comparing with other advanced methods, our model reaches the state of the art in the combined metrics of recognition accuracy, the number of parameters, and inference speed. First, we propose AMI-NanoNet based on Roofline theory to significantly reduce the number of parameters and computational complexity. This model can achieve 99.8343% accuracy on PlantVillage by using a feature-guided curriculum learning with stepwise training strategy. Moreover, we design another training strategy suitable for lightweight ensemble models. Based on this strategy, our model only needs to integrate the classifiers at the end of the network to achieve 99.8708% identification accuracy, and it hardly increases the number of operations and parameters of the network. Extensive evaluations on this dataset demonstrate the effectiveness of our ensemble learning method. Furthermore, we tested our proposed methods on another dataset from other domains to validate its applicability to different scenarios. Overall, our research provides a basis for rapid and intelligent identification of plant diseases. © 2023 IEEE.

关键词： Real time systems

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Accurate RGB-D SLAM in dynamic environments based on dynamic visual feature removal

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Science China(Information Sciences) 2022年第10期65卷 256-269页

作者： Chenxin LIU Jiahu QIN Shuai WANG Lei YU Yaonan WANG Department of Automation University of Science and Technology of China Institute of Artificial Intelligence Hefei Comprehensive National Science Center College of Electrical and Information Engineering Hunan University National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University

visual localization is considered an essential capability in robotics and has attracted increasing interest for the past few years. However, most proposed visual localization systems assume that the surrounding environment is static, which is difficult to maintain in real-world scenarios due to the presence of moving objects. In this paper, we present DFR-SLAM, a real-time and accurate RGB-D SLAM based on ORB-SLAM2 that achieves satisfactory performance in a variety of challenging dynamic scenarios. At the core of our system lies a motion consensus filtering algorithm estimating the initial camera pose and a graph-cut optimization framework combining long-term observations, prior information, and spatial coherence to jointly distinguish dynamic and static visual features. Other systems for dynamic environments detect dynamic components by using the information from short time-span frames, whereas our system uses observations from a long period of keyframes. We evaluate our system using dynamic sequences from the public TUM dataset, and the evaluation demonstrates that the proposed system outperforms the original ORB-SLAM2 system significantly. In addition, our system provides competitive localization accuracy with satisfactory real-time performance compared to closely related SLAM systems designed to adapt to dynamic environments.

关键词： SLAM dynamic environments indoor localization graph-cut robot navigation

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Adaptive Impedance control for Mobile Cooperative Manipulation Systems With Stability and Passivity Guarantees*

Adaptive Impedance Control for Mobile Cooperative Manipulati...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Danping Zeng Yaonan Wang Yiming Jiang Haoran Tan Zhiqiang Miao Yun Feng School of Robotics and the National Engineering Research Center for Robot Visual Perception and Control Technology Hunan University Changsha China College of Electrical and Information Engineering and the National Engineering Research Center for Robot Visual Perception and Control Technology Hunan University Changsha China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

A number of robotic tasks exist, such as manipulating heavy and oversized objects, where a single manipulator is not enough and multiple mobile manipulators need to be used. When uncertainty exists, a compliant control strategy is expected to be applied for such a tightly coordinated multiple mobile manipulator system. An adaptive impedance control law that enables adaptive updating of impedance parameters is developed in this work. The proposed method ensures that all closed-loop systems boundedly and asymptotically realize the desired adaptive impedance dynamics. Furthermore, to ensure the passivity of the adaptive impedance system, the impedance system of each mobile manipulator is interconnected with a virtual energy tank, and the update of the impedance system parameters is guided according to the level of the energy to ensure that the adaptive impedance system is passive, thus realizing the adaptive trade-off between compliance and operational accuracy. Finally, a simulation for four mobile manipulators collaborating to carry an unknown object is provided to validate the effectiveness of the proposed one.

关键词： Adaptive systems Uncertainty Mechatronics robot kinematics Cooperative systems Stability analysis Trajectory Impedance Closed loop systems Manipulator dynamics

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Current Status,Challenges,and Prospects for New Types of Aerial robots

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engineering 2024年第10期41卷 19-34页

作者： Xidong Zhou Hang Zhong Hui Zhang Wei He Hean Hua Yaonan Wang College of Robotics Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China School of Intelligence Science and Technology Beijing University of Science and TechnologyBeijing 100083China

New types of aerial robots(NTARs)have found extensive applications in the military,civilian contexts,scientific research,disaster management,and various other *** with traditional aerial robots,NTARs exhibit a broader range of morphological diversity,locomotion capabilities,and enhanced operational ***,this study defines aerial robots with the four characteristics of morphability,biomimicry,multi-modal locomotion,and manipulator attachment as ***,this paper discusses the latest research progress in the materials and manufacturing technology,actuation technology,and perception and control technology of ***,the research status of NTAR systems is summarized,focusing on the frontier development and application cases of flapping-wing microair vehicles,perching aerial robots,amphibious robots,and operational aerial ***,the main challenges presented by NTARs in terms of energy,materials,and perception are analyzed,and the future development trends of NTARs are summarized in terms of size and endurance,mechatronics,and complex scenarios,providing a reference direction for the follow-up exploration of NTARs.

关键词： Aerial robot Morphability Biomimicry Perch Amphibious

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Within-Hand Manipulation with an Underactuated Dexterous Hand Based on Pre-Trained Reinforcement Learning

Within-Hand Manipulation with an Underactuated Dexterous Han...

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Chinese Automation Congress (CAC)

作者： Xin Li Wenrui Chen Yaonan Wang Qiang Diao Sijie Wu Fan Yang National Engineering Research Center for Robot Visual Perception and Control College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control School of Robotics Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control College of Mechanical and Vehicle Engineering Hunan University Changsha China

This paper investigates a dexterous manipulation method for multi-fingered hands based on the approximate policy optimization (PPO) algorithm. First, a prior knowledge base of dexterous manipulation demonstration data is provided for the PPO algorithm, and the original model is pre-trained to guide fast network training. Second, a new reward function is proposed to optimize rotational manipulation action decisions based on hand joints, fingertip tactile, and object pose infor mation. Finally, a three-fingered hand is used as an example for rotational manipulation experiments, and the comparative simulation results show that the method is more efficient than the traditional PPO algorithm and provides ideas for dexterous manipulation of multi-fingered hands.

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