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Journal of Robotics最新文献

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Visual Localization of an Internal Inspection Robot for the Oil-Immersed Transformer 油浸式变压器内部检测机器人的可视化定位系统
IF 1.8 Q4 ROBOTICS Pub Date : 2023-12-29 DOI: 10.1155/2023/6699265
Yingbin Feng, Yahui Kou, Yanju Liu
Aiming at the problem that the robot is difficult to locate in the oil-immersed transformer, a visual positioning of the robot is proposed for internal inspection. First, in order to solve the problem of blur, distortion, and low contrast of the image obtained by the camera in the deteriorated and discolored transformer oil, an image enhancement algorithm based on multiscale fusion is developed to provide a reliable data source for robot localization. Then, the FAST key points are extracted and the BRIEF descriptors are calculated from the enhanced images, and the pose transformation of the robot between image frames is calculated by using polar constraint and EPnP method. A pose optimization model of the robot is designed to improve the positioning accuracy. Finally, to verify the effectiveness of the proposed methods, function tests are carried out by using the real continuous image sequence acquired by the robot in Mitsubishi transformer. The experimental results show that the trajectory of the robot in the transformer can be accurately drawn, the position data of the robot can be efficiently obtained, and autonomous positioning of the robot in the transformer can be well achieved.
针对机器人在油浸式变压器中难以定位的问题,提出了一种机器人视觉定位的内部检测方法。首先,为了解决变质变色变压器油中摄像头获取的图像模糊、失真和对比度低的问题,开发了一种基于多尺度融合的图像增强算法,为机器人定位提供可靠的数据源。然后,从增强后的图像中提取 FAST 关键点并计算 BRIEF 描述符,利用极性约束和 EPnP 方法计算机器人在图像帧间的姿态变换。设计了机器人姿态优化模型,以提高定位精度。最后,为了验证所提方法的有效性,使用机器人在三菱变压器中获取的真实连续图像序列进行了功能测试。实验结果表明,机器人在变压器中的运动轨迹可以精确绘制,机器人的位置数据可以有效获取,机器人在变压器中的自主定位可以很好地实现。
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引用次数: 0
Retracted: Online Control Method of Small- and Medium-Sized Electromechanical Equipment Based on Deep Neural Network 撤回:基于深度神经网络的中小型机电设备在线控制方法
IF 1.8 Q4 ROBOTICS Pub Date : 2023-12-20 DOI: 10.1155/2023/9827679
Journal of Robotics
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引用次数: 0
Retracted: Application of 5G Mobile Communication Technology Integrating Robot Controller Communication Method in Communication Engineering 撤回:结合机器人控制器通信方法的 5G 移动通信技术在通信工程中的应用
IF 1.8 Q4 ROBOTICS Pub Date : 2023-12-20 DOI: 10.1155/2023/9780273
Journal of Robotics
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引用次数: 0
Retracted: Machinery Changes and Challenges of Architecture and Landscape Design in the Virtual Reality Perspective 撤回:虚拟现实视角下建筑与景观设计的机械变革与挑战
IF 1.8 Q4 ROBOTICS Pub Date : 2023-12-20 DOI: 10.1155/2023/9824265
Journal of Robotics
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引用次数: 0
Retracted: The Application of Multimedia Visualization Platform in Business Management from the Perspective of Supply Chain Management 撤回:从供应链管理角度看多媒体可视化平台在企业管理中的应用
IF 1.8 Q4 ROBOTICS Pub Date : 2023-12-20 DOI: 10.1155/2023/9852312
Journal of Robotics
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引用次数: 0
Retracted: Designing and Manufacturing of Industrial Robots with Dual-Angle Sensors Taking into Account Vibration Signal Fusion 撤回:考虑振动信号融合因素,设计和制造带双角传感器的工业机器人
IF 1.8 Q4 ROBOTICS Pub Date : 2023-12-20 DOI: 10.1155/2023/9768015
Journal of Robotics
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引用次数: 0
Retracted: Analysis and Evaluation of Ecological Environment Monitoring Based on PIE Remote Sensing Image Processing Software 撤回:基于 PIE 遥感图像处理软件的生态环境监测分析与评估
IF 1.8 Q4 ROBOTICS Pub Date : 2023-12-20 DOI: 10.1155/2023/9874013
Journal of Robotics
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引用次数: 0
Backstepping Sliding Mode Control Algorithm for Unmanned Aerial Vehicles Based on Fractional-Order Theory 基于分数阶理论的无人机反步进滑模控制算法
IF 1.8 Q4 ROBOTICS Pub Date : 2023-11-30 DOI: 10.1155/2023/1388072
Yanzhu Zhang, Bo Zhuang, Chunhao Ma, Cheng Zhang
Aiming at the problems of slow convergence speed and low tracking accuracy in attitude control and position tracking of quadrotor unmanned aerial vehicles (UAVs). This paper combines the fractional-order calculus theory with the backstepping sliding mode control algorithm, using the backstepping control to compensate for the nonlinearity of the system and the fractional-order theory to eliminate the jitter brought about by the sliding mode control, and proposes a new fractional-order backstepping sliding mode control strategy for the trajectory tracking control of the quadrotor UAV. The proposed fractional-order sliding mode surface increases the control flexibility and improves the robustness and anti-interference ability of the system to some extent. The stability analysis of the system is carried out using the Lyapunov stability theory, and the results prove the stability of the proposed controller. Finally, the effectiveness and feasibility of the proposed method are verified by comparing it with the traditional backstepping sliding mode controller. The simulation results show that the fractional-order reverse-step sliding mode control algorithm proposed in this paper is significantly better than other control algorithms in terms of convergence speed and also has a certain degree of superiority in terms of error elimination.
针对四旋翼无人飞行器(UAV)姿态控制和位置跟踪中收敛速度慢、跟踪精度低的问题。本文将分数阶微积分理论与反步滑模控制算法相结合,利用反步控制补偿系统的非线性,利用分数阶理论消除滑模控制带来的抖动,提出了一种新的分数阶反步滑模控制策略,用于四旋翼无人机的轨迹跟踪控制。所提出的分数阶滑动模态面增加了控制的灵活性,在一定程度上提高了系统的鲁棒性和抗干扰能力。利用 Lyapunov 稳定性理论对系统进行了稳定性分析,结果证明了所提控制器的稳定性。最后,通过与传统的反步进滑模控制器进行比较,验证了所提方法的有效性和可行性。仿真结果表明,本文提出的分数阶反向步进滑模控制算法在收敛速度方面明显优于其他控制算法,在误差消除方面也具有一定的优越性。
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引用次数: 0
The Parallel Solving Method of Robot Kinematic Equations Based on FPGA 基于FPGA的机器人运动方程并行求解方法
Q4 ROBOTICS Pub Date : 2023-11-03 DOI: 10.1155/2023/2426982
Deli Zhang, Shaohua Jiang, Liu Zhe
In the implementation of robot motion control, complex kinematic computations consume too much central processing unit (CPU) time and affect the responsiveness of robot motion. To solve this problem, this paper proposes a parallel method for solving kinematic equations of articulated robots based on the coordinate rotation digital computer (CORDIC) algorithm. The method completes the fast calculation of the transcendental function based on the CORDIC algorithm, adopts the tree structure method to optimize the key computational paths of forward and inverse solutions, and designs a parallel pipeline to realize the low latency and high throughput of the kinematic equations. The experiments of the proposed method are validated based on the field-programmable gate array (FPGA) hardware experimental platform, and the experimental results demonstrate that the computational time to complete the entire kinematic equations is 4.68 μs, of which the computational time for the kinematic positive solution is 0.52 μs and the computational time for the kinematic inverse solution is 4.16 μs.
在机器人运动控制的实现中,复杂的运动学计算消耗了过多的CPU时间,影响了机器人运动的响应性。为了解决这一问题,本文提出了一种基于坐标旋转数字计算机(CORDIC)算法求解关节机器人运动方程的并行方法。该方法基于CORDIC算法完成超越函数的快速计算,采用树形结构方法优化正解和反解的关键计算路径,并设计并行流水线实现运动方程的低延迟和高吞吐量。基于现场可编程门阵列(FPGA)硬件实验平台对所提方法进行了实验验证,实验结果表明,完成整个运动学方程的计算时间为4.68 μs,其中运动学正解的计算时间为0.52 μs,运动学逆解的计算时间为4.16 μs。
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引用次数: 0
Retracted: Research on Clue Mining in Criminal Cases of Smart Phone Trojan Horse under the Background of Information Security 撤下:信息安全背景下智能手机特洛伊木马犯罪案件线索挖掘研究
Q4 ROBOTICS Pub Date : 2023-10-18 DOI: 10.1155/2023/9785409
Journal of Robotics
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引用次数: 0
期刊
Journal of Robotics
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