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Journal of Robotics最新文献

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Kinematics Model Estimation of 4W Skid-Steering Mobile Robots Using Visual Terrain Classification 基于视觉地形分类的4W滑移转向移动机器人运动学模型估计
Q4 ROBOTICS Pub Date : 2023-10-11 DOI: 10.1155/2023/1632563
Yang Chen, Yao Wu, Wei Zeng, Shaoyi Du
Accurate real-time kinematics model is very important for the control of a skid-steering mobile robot. In this study, the kinematics model of the skid-steering mobile robots was first designed based on instantaneous rotation centers (ICRs). Then, the extended Kalman filter (EKF) technique was applied to obtain the parameters of ICRs under the same specific terrain online. To adapt to different terrain environments, the fractal dimension-based SFTA (segmentation-based fractal texture analysis) method was used to extract features of different terrains, and the k-nearest neighbor (KNN) method was used to classify the terrains. In the case of real-time terrain recognition, the filter parameters of the EKF for estimating the ICRs are adjusted adaptively. Experiments on a real skid-steering mobile robot show that this method can quickly estimate the kinematics model of the robot in the case of terrain changes, and can meet the needs of practical applications. The average error of odometer estimation based on visual terrain classification is 0.06 m, while the average error of odometer estimation without terrain classification is 0.14 m.
准确的实时运动学模型对滑移转向移动机器人的控制至关重要。本研究首先基于瞬时旋转中心(ICRs)设计了滑移转向移动机器人的运动学模型。然后,应用扩展卡尔曼滤波(EKF)技术在线获取相同特定地形下的icr参数;为了适应不同的地形环境,采用基于分形维数的SFTA(分段分形纹理分析)方法提取不同地形的特征,并采用k近邻(KNN)方法对地形进行分类。在实时地形识别的情况下,自适应调整EKF估计icr的滤波器参数。在实际滑动转向移动机器人上的实验表明,该方法能够快速估计出地形变化情况下机器人的运动学模型,能够满足实际应用的需要。基于视觉地形分类的里程表估计平均误差为0.06 m,而不进行地形分类的里程表估计平均误差为0.14 m。
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引用次数: 0
Retracted: Research on the Detection Countermeasures of Telecommunication Network Fraud Based on Big Data for Killing Pigs and Plates 撤下:基于杀猪杀盘大数据的电信网络诈骗检测对策研究
Q4 ROBOTICS Pub Date : 2023-09-20 DOI: 10.1155/2023/9860830
Journal of Robotics
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引用次数: 0
Retracted: Evaluation of the Students’ Learning Status in the Foreign Language Classroom Based on Machine Vision 基于机器视觉的外语课堂学生学习状态评价
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/9857401
Journal of Robotics
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引用次数: 0
Retracted: Recognition and Modeling of Crisis Propagation Patterns Combined with Robot Simulation of Social Networks 基于机器人社会网络仿真的危机传播模式识别与建模
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/9768653
Journal of Robotics
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引用次数: 0
Design of a Novel NNs Learning Tracking Controller for Robotic Manipulator with Joints Flexibility 具有关节柔性的机器人神经网络学习跟踪控制器设计
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/1186719
Pengxiao Jia
The precise tracking control problem for the robotic manipulator with flexible joints, subjected to system uncertainties and external disturbances, is addressed. A novel control scheme is presented that does not use link velocity measurements and high-order derivatives of the link states. The control scheme employs neural networks-based observers to estimate both motor velocity and link velocity. By using the virtually applied torque, the link controller is designed based on rigid link dynamics, and the motor controller is designed using the dynamic surface control technique. The proposed control scheme can guarantee that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The simulation results confirm our theoretical analysis, and a comparison study demonstrates the advantages of the proposed control scheme compared to the standard DSC method.
研究了柔性关节机械手在系统不确定性和外部扰动作用下的精确跟踪控制问题。提出了一种新的控制方案,该方案不使用链路速度测量和链路状态的高阶导数。该控制方案采用基于神经网络的观测器来估计电机速度和连杆速度。利用虚拟施加的转矩,基于刚性连杆动力学设计了连杆控制器,利用动态曲面控制技术设计了电机控制器。所提出的控制方案可以保证闭环系统中的所有信号都是半全局一致最终有界的,并且跟踪误差最终收敛到零附近的一个小邻域。仿真结果证实了我们的理论分析,并通过比较研究证明了所提出的控制方案与标准DSC方法相比的优势。
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引用次数: 0
Retracted: A Russian Continuous Speech Recognition System Based on the DTW Algorithm under Artificial Intelligence 人工智能下基于DTW算法的俄语连续语音识别系统
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/9832350
Journal of Robotics
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引用次数: 0
Retracted: Deep Learning BP Neural Network Guided Evaluation of Students’ Innovation and Entrepreneurship Education 收回:深度学习BP神经网络引导学生创新创业教育评价
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/9845964
Journal of Robotics
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引用次数: 0
Retracted: Multiscale Motion Detection and Recognition Combining Still Images and Video Sequences 撤下:结合静止图像和视频序列的多尺度运动检测和识别
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/9896453
Journal of Robotics
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引用次数: 0
Retracted: The Evaluation of Visual Clarity and Comfort of Light Environment in Multimedia Classroom 退缩:多媒体教室光环境的视觉清晰度与舒适性评价
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/9807401
Journal of Robotics
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引用次数: 0
Retracted: Discussion on Redundant Processing Algorithm of Association Rules Based on Hypergraph in Data Mining 数据挖掘中基于超图的关联规则冗余处理算法探讨
IF 1.8 Q4 ROBOTICS Pub Date : 2023-08-09 DOI: 10.1155/2023/9789505
Journal of Robotics
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引用次数: 0
期刊
Journal of Robotics
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