检索结果-内蒙古大学图书馆

Nonsingular Fixed-Time Attitude Tracking Control for Rigid Spacecraft

IEEE Transactions on Aerospace and Electronic Systems 2025年第3期61卷 6839-6855页

作者： Dong, Rui-Qi Wu, Ai-Guo Qi, Wen-Nian Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China

In this article, the nonsingular fixed-time control (NFTC) and unwinding problem for rigid spacecraft attitude tracking are investigated. By introducing dynamic powers, a class of sliding functions and a class of NFTC laws are proposed. In particular, dynamic powers in the developed sliding functions are constructed by the elements of the quaternion, and dynamic powers in the presented control laws are composed of the norm of the sliding function. Specifically, a sliding function is developed to ensure that the sliding surface has exactly one equilibrium point. Correspondingly, a nonsingular controller is proposed to guarantee that the obtained closed-loop system is almost globally fixed-time stable. In order to handle the unwinding problem, another sliding function is presented such that the sliding surface contains two stable equilibria. Accordingly, an antiunwinding fixed-time attitude tracking controller is developed such that the set of two stable equilibria is almost globally fixed-time stable. Moreover, adjustable subsets of the attraction regions of two stable equilibria are provided. Finally, numerical simulations are performed to validate the significance of the designed control laws. © 1965-2011 IEEE.

关键词： Control theory

来源：评论

学校读者我要写书评

暂无评论

PCE: Multi-Agent Path Finding via Priority-Aware Communication & Experience Learning

IEEE Transactions on Intelligent Vehicles

引用

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

来源：评论

学校读者我要写书评

暂无评论

Aircraft Engine Remaining Useful Life Prediction Using Attention-Based Convolutional Neural Network - Gated Recurrent Unit

Aircraft Engine Remaining Useful Life Prediction Using Atten...

引用

TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Sun, Shilong Ding, Hao Huang, Haodong Guangdong Shenzhen518055 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Guangdong Shenzhen518055 China

ISBN: (纸本)9783031702341

As aircraft usage time increases, the state and performance of aircraft engines gradually deteriorate. In the context of rapid development in smart industries and aviation transport, accurate assessment of aircraft engine status and prediction of Remaining Useful Life (RUL) are crucial for flight safety and maintenance cost reduction. This study focuses on the multivariate time series features of historical data from aircraft engines. It develops an RUL prediction model based on the Convolutional Neural Network-Gated Recurrent Unit (CNN-GRU) model integrated with an attention mechanism to enhance the focus on key features. Through training and testing on real engine datasets, the effectiveness and accuracy of the proposed method in RUL prediction tasks were validated. Experimental findings demonstrate that the proposed method offers relatively precise predictions of engine RUL, furnishing vital decision support and optimization strategies for airlines and maintenance teams. This research holds significant implications for enhancing flight operational safety, refining maintenance schedules, and reducing operational costs, presenting extensive prospects within the aerospace engineering domain. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Aggressive and robust low-level control and trajectory tracking for quadrotors with deep reinforcement learning

引用

Neural Computing and Applications 2025年第3期37卷 1223-1240页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Department of Control Science and Engineering Harbin Institute of Technology Shenzhen Shenzhen518055 China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China

Executing accurate trajectory tracking tasks using a high-performance low-level controller is crucial for quadrotors to be applied in various scenarios, especially those involving uncertain disturbances. However, due to the uncertainties in disturbed environments, developing effective low-level controllers with traditional model-based control schemes is challenging. This paper presents an aggressive and robust reinforcement learning (RL)-based low-level control policy for quadrotors. The policy maps the observed quadrotor state directly to motor thrust commands, without requiring the quadrotor dynamics. Additionally, a trajectory generation pipeline is developed to improve the accuracy of trajectory tracking tasks based on differential flatness. With the learned low-level control policy, extensive simulations and real-world experiments are implemented to validate the performance of the policy. The results indicate that our RL-based low-level control policy outperforms traditional proportional–integral–derivative (PID) control methods and related learning-based policies in terms of accuracy and robustness, particularly in environments with uncertain disturbances. Furthermore, the proposed RL-based control policy exhibits an aggressive response in trajectory tracking, even when the speed of the desired trajectory is increased to 6 m/s. Moreover, the learned policy demonstrates strong vibration suppression capabilities and enables the quadrotor to recover to a hovering state from random initial conditions with shorter response time. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Fault Feature Extraction Based on Unsupervised Graph Embedding for Harmonic Reducers Diagnosis 2nd

Fault Feature Extraction Based on Unsupervised Graph Embeddi...

引用

2nd International Conference of Mechanical System Dynamics, ICMSD 2023

作者： Sun, Shilong Ding, Hao Guangdong Province Shenzhen City518055 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Guangdong Province Shenzhen City518055 China

ISBN: (纸本)9789819980475

In recent years, there has been a growing interest in data-driven intelligent fault diagnosis, focusing on extracting fault features, which has emerged as a critical and challenging aspect of fault diagnosis. However, most existing intelligent diagnostic methods are supervised, relying on many labeled samples and treating them as independent entities, disregarding their correlations. Moreover, the failure of harmonic reducers, as crucial components in robots, can significantly impact the performance and practical applications of the robots. To address these issues, we proposed an unsupervised feature extraction method based on graph embedding, utilizing vibration signal data from harmonic reducers in this study. Specifically, a graph data structure was constructed based on the specific context, and a graph convolutional autoencoder approach was employed to learn representations of subgraphs that captured the sample data, resulting in low-dimensional vector representations of the vibration signals. In the final stage, the extracted features were treated as labeled samples. A subset comprising only 6% of the available samples was used to train several simple models. Subsequently, the remaining sample data was employed for testing purposes. The experimental results demonstrated notably higher accuracy in fault diagnosis, thereby providing strong empirical evidence to validate the effectiveness of the proposed approach. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

How Collective Intelligence Emerges in a Crowd of People Through Learned Division of Labor: A Case Study

How Collective Intelligence Emerges in a Crowd of People Thr...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Wang, Dekun Zhang, Hongwei School of Mechanical Engineering and Automation Harbin Institute of Technology Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Guangdong Shenzhen518055 China

ISBN: (纸本)9781665410205

This paper investigates the factors fostering collective intelligence (CI) through a case study of *LinVi's Experiment, where over 2000 human players collectively controll an avatar car. By conducting theoretical analysis and replicating observed behaviors through numerical simulations, we demonstrate how self-organized division of labor (DOL) among individuals fosters the emergence of CI and identify two essential conditions fostering CI by formulating this problem into a stability problem of a Markov Jump Linear System (MJLS). These conditions, independent of external stimulus, emphasize the importance of both elite and common players in fostering CI. Additionally, we propose an index for emergence of CI and a distributed method for estimating joint actions, enabling individuals to learn their optimal social roles without global action information of the whole crowd. © 2024 IEEE.

关键词： Linear systems

来源：评论

学校读者我要写书评

暂无评论

Bearing-Only Formation Tracking Control With Time-Varying Leaders' Velocity without Inter-Agent Communication 43

Bearing-Only Formation Tracking Control With Time-Varying Le...

引用

43rd Chinese Control Conference, CCC 2024

作者： Huang, Yuxiao Chen, Tianxing Zhang, Hongwei Harbin Institute of Technology Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics School of Mechanical Engineering and Automation Guangdong Shenzhen518055 China

ISBN: (纸本)9789887581581

This paper studies the bearing-only formation tracking problem of leader-follower multi-agent systems, where the leaders move at a time-varying velocity. Different from the existing formation tracking methods, the proposed control protocol can be implemented without inter-agent communication. We construct the control protocol via a variable structure approach to track the time-varying velocity and almost achieve the target formation. We also show that the velocity tracking error will converge to zero and the position tracking error can be restricted in an upper bounded set while the upper bound can be arbitrarily minimized by increasing the control gain. Simulation results are presented to illustrate the effectiveness of the control protocol. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

Fusing Dynamics and Reinforcement Learning for Control Strategy: Achieving Precise Gait and High Robustness in Humanoid Robot Locomotion 23

Fusing Dynamics and Reinforcement Learning for Control Strat...

引用

23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Zhao, Zida Huang, Haodong Sun, Shilong Li, Chiyao Xu, Wenfu Harbin Institute of Technology Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics School of Mechanical Engineering and Automation Shenzhen518055 China

ISBN: (纸本)9798350373578

Achieving precise gait planning and high robustness in locomotion control is crucial for the development and application of humanoid robots. In this paper, a novel control strategy is proposed, which combines dynamics control and reinforcement learning (RL), leveraging the precision of dynamics control and the robustness of RL. Specifically, foot placements for each step of the humanoid robot are designed, and the trajectories of the center of mass (CoM) and feet are obtained using a 3D linear inverted pendulum model (3D LIPM). Subsequently, joint angles during motion are calculated based on the trajectories of the CoM and feet using inverse kinematics equations. Finally, the obtained joint angles are trained as baseline actions using RL algorithms. To enhance control robustness, parameter domain randomization is introduced during the training process. By employing this control strategy, simulations of various single-step gaits, such as walking forward, walking to the right, and making right turns, are achieved. Additionally, trajectory tracking, locomotion tests on different terrains, and disturbance resistance are conducted. The simulation results demonstrate that the proposed control strategy enables precise gait control and exhibits strong robustness in humanoid robots. © 2024 IEEE.

关键词： Inverse kinematics

来源：评论

学校读者我要写书评

暂无评论

intelligent Fault Diagnosis Method of Robot Joint—Harmonic Reducer Based on EMD and SVM 17th

Intelligent Fault Diagnosis Method of Robot Joint—Harmonic ...

引用

17th World Congress on Engineering Asset Management, WCEAM 2023

作者： Zhao, Zida Sun, Shilong Guangdong Province Shenzhen City518055 China Guangdong Provincial Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Guangdong Province Shenzhen City518055 China

ISBN: (纸本)9783031590412

The harmonic reducer is a vital component of a robot, responsible for high-precision and high-torque transmission. It finds wide applications in the field of robotics. However, due to its complex internal structure and the generation of significant friction and heat during operation, it is prone to failures that can significantly impact the robot’s performance. To address this issue, we propose a fault diagnosis method based on empirical mode decomposition (EMD) and support vector machine (SVM). The proposed method involves several steps. First, the fault data are decomposed using EMD, and the resulting intrinsic mode functions (IMFs) are evaluated based on their steepness values and correlation with the original signal. Only the most relevant IMFs are selected for reconstruction. Next, the reconstructed signal is band-pass filtered according to the recommended centre frequency and bandwidth parameters. The filtered signal is then demodulated using square envelope analysis. Then, time-domain and frequency-domain features of the demodulated square envelope signal are extracted and used as inputs for training and testing an SVM classifier. The SVM classifier learns to associate these features with specific fault types or normal operations, enabling fault identification. Finally, a comparative experiment is conducted to evaluate the performance of the proposed method. The results demonstrate that the method achieves high accuracy in fault identification for the harmonic reducer. This approach provides theoretical support for ensuring the safe operation of both the harmonic reducer and the robot as a whole. © International Society of Engineering Asset Management 2024.

关键词： Frequency domain analysis

来源：评论

学校读者我要写书评

暂无评论

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

引用

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)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：