With the rapid development of deep learning, it has been widely applied in fields such as computer vision, natural language processing, and robotics. Despite the superior performance of deep learning in object detecti...
详细信息
This paper deal with the end-point steady control problem of a mobile manipulators(MM) at the velocity level. Mobile manipulators are usually kinematically redundant when performing tasks, so multiple subtasks can be ...
This paper deal with the end-point steady control problem of a mobile manipulators(MM) at the velocity level. Mobile manipulators are usually kinematically redundant when performing tasks, so multiple subtasks can be performed simultaneously, such as tracking the trajectory of the end effector(EE), optimizing manipulability, etc. First, the mobile manipulators system is modeled as an ordinary jointed manipulator. The velocity of the EE has a higher priority, scheduling low-priority tasks in the null space of high-priority tasks leaves high-priority tasks unaffected. The damped least square method is used to generate a kinematic inverse solution with singular robustness, and the gradient projection method is used to optimize the manipulability measure. By analyzing the structure of the Jacobian matrix, the complexity of gradient calculation is reduced. Finally, the effectiveness of the proposed algorithm is verified by simulation experiments.
An optimized YOLOX+DeepSORT method is proposed to accurately detect and track container trucks and truck drivers at the working position of automated rubber tire gantries in ports, while ensuring their safety during t...
An optimized YOLOX+DeepSORT method is proposed to accurately detect and track container trucks and truck drivers at the working position of automated rubber tire gantries in ports, while ensuring their safety during the whole working *** the proposed method, the improved YOLOX performs object detection and its output is used as the input for multi-object tracking using DeepSORT. The improved YOLOX model is developed through replacing standard convolution with depthwise separable convolution, adding the convolutional block attention module to enhance feature extraction, and using Focal Loss in the loss function to address sample imbalances. Comparative experiments were carried out on a self-built dataset, showing a4.32% increase in mAP and improved reasoning speed for improved YOLOX compared to the original YOLOX. Furthermore,the optimized method shows a 3.57% increase in Multi-Object Tracking Accuracy and a 1.73% increase in Multi-Object Tracking Precision compared to the benchmark YOLOX+DeepSORT.
To realize dual-robot autonomous path planning and realization, the trajectory planning research of dual-robot is carried out using the open-source robot operating system ROS as the simulation platform. The motion pla...
To realize dual-robot autonomous path planning and realization, the trajectory planning research of dual-robot is carried out using the open-source robot operating system ROS as the simulation platform. The motion planning-related file configuration is completed by using MoveIt! In trajectory planning, cubic spline interpolation is performed on the trajectory points generated by the RRT-Connect path planning algorithm to complete the planning of the dual-arm assembly task. The communication between ROS nodes and ROS is established in the controller, and the processed trajectory points are communicated with the controller through ROS-Industrial. The experimental results show that the trajectory of the dual robot movement process is smooth and continuous, the stability is strong, and the error is small, which can ensure the completion of basic assembly tasks.
In this study, we investigate the control problem of electronic throttle systems in the presence of practical challenges such as disturbances and measurement noises. To address these challenges, we propose an adaptive...
In this study, we investigate the control problem of electronic throttle systems in the presence of practical challenges such as disturbances and measurement noises. To address these challenges, we propose an adaptive augmented Kalman filter(AAKF)based control approach that combines the strengths of extended state observer in disturbance estimation and adaptive Kalman filter in adaptive noise filtering. The outputs of AAKF are integrated into the Backstepping control design, resulting in a composite control that concurrently achieves fast disturbance rejection and noise suppression. We conduct a comparative simulation study against conventional methods without adaptive filtering to validate the effectiveness of the proposed AAKF-based control strategy, which exhibits superior position control accuracy and disturbance attenuation performance. We envision that our proposed control strategy will contribute to improving vehicle power, fuel economy, and emission performance.
In order to address the problem of current object detection models being too large to be deployed on robot controllers, this paper proposes improvements to YOLOv5 for real-time detection. The YOLOv5s model is pruned a...
详细信息
With the improvement of communication technology and the management of demand-side, more and more researches focus on the aggregation technology of flexible resources on the demand side. This paper proposes to build a...
详细信息
The development of the scientific publishing system has remarkably enhanced global accessibility to research findings and substantially increased the visibility and dissemination of academic publications. However, sig...
详细信息
Quantum computing has grown substantially over the past four decades, but whether it can outperform classical methods in practical use remains uncertain [1]. Fluid dynamics simulation, challenging in classical physics...
Quantum computing has grown substantially over the past four decades, but whether it can outperform classical methods in practical use remains uncertain [1]. Fluid dynamics simulation, challenging in classical physics but vital for applications, is a potential area for showcasing quantum advantage. The quantum computing for fluid dynamics (QCFD)[2]is expected to efficiently simulate intricate turbulent flows with high Reynolds numbers. This capability is crucial for critical applications, including aircraft design and weather forecast.
Semantic SLAM can achieve the acquisition of environmental semantic information and increase the understanding of the environmental content. Therefore, it has received extensive attention from academia and industry. I...
详细信息
暂无评论