The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly fa...The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.展开更多
The measurement of position and attitude parameters for the isolated target from a highspeed aircraft is a great challenge in the field of wind tunnel simulation technology. This paper proposes a remote-controlled fle...The measurement of position and attitude parameters for the isolated target from a highspeed aircraft is a great challenge in the field of wind tunnel simulation technology. This paper proposes a remote-controlled flexible pose measurement system in wind tunnel conditions for the separation of a target from an aircraft. The position and attitude parameters of a moving object are obtained by utilizing a single camera with a focal length and camera orientation that can be changed based on different measurement conditions. Using this proposed system and method, both the flexibility and efficiency of the pose measurement system can be enhanced in wind tunnel conditions to meet the measurement requirements of different objects and experiments, which is also useful for the development of an intelligent position and attitude measurement system. The position and the focal length of the camera also can be controlled remotely during measurements to enlarge both the vertical and horizontal measurement range of this system. Experiments are conducted in the laboratory to measure the position and attitude of moving objects with high flexibility and efficiency, and the measurement precision of the measurement system is also verified through experiments.展开更多
Due to the portability and anti-interference ability,vision-based shipborne aircraft automatic landing systems have attracted the attention of researchers.In this paper,a Monocular Camera and Laser Range Finder(MC-LRF...Due to the portability and anti-interference ability,vision-based shipborne aircraft automatic landing systems have attracted the attention of researchers.In this paper,a Monocular Camera and Laser Range Finder(MC-LRF)-based pose measurement system is designed for shipborne aircraft automatic landing.First,the system represents the target ship using a set of sparse landmarks,and a two-stage model is adopted to detect landmarks on the target ship.The rough 6D pose is measured by solving a Perspective-n-Point problem.Then,once the rough pose is measured,a region-based pose refinement is used to continuously track the 6D pose in the subsequent image sequences.To address the low accuracy of monocular pose measurement in the depth direction,the designed system adopts a laser range finder to obtain an accurate range value.The measured rough pose is iteratively optimized using the accurate range measurement.Experimental results on synthetic and real images show that the system achieves robust and precise pose measurement of the target ship during automatic landing.The measurement means error is within 0.4in rotation,and 0.2%in translation,meeting the requirements for automatic fixed-wing aircraft landing.展开更多
An event-triggered moving horizon estimation strategy is proposed for spacecraft pose estimation.The error dual quaternion is used to describe the system state and construct the spacecraft attitude-orbit coupled model...An event-triggered moving horizon estimation strategy is proposed for spacecraft pose estimation.The error dual quaternion is used to describe the system state and construct the spacecraft attitude-orbit coupled model.In order to reduce the energy consumption on spacecraft,an event-triggered moving horizon estimator(MHE)is designed for real-time pose estimation with limited communication resources.The model mismatch caused by event-triggered is finally solved by solving the cost function of the min-max optimization problem.The system simulation model is built in Matlab/Simulink,and the spacecraft pose estimation simulation is carried out.The numerical results demonstrate that the designed estimator could ensure the estimation effect and save spacecraft communication and computing resources effectively.展开更多
Two dynamical system methods are studied for solving linear ill-posed problems with both operator and right-hand nonexact. The methods solve a Cauchy problem for a linear operator equation which possesses a global sol...Two dynamical system methods are studied for solving linear ill-posed problems with both operator and right-hand nonexact. The methods solve a Cauchy problem for a linear operator equation which possesses a global solution. The limit of the global solution at infinity solves the original linear equation. Moreover, we also present a convergent iterative process for solving the Cauchy problem.展开更多
This work presents a mapping and tracking system based on images to enable a small Unmanned Aerial Vehicle(UAV)to accurately navigate in indoor and GPS-denied outdoor environments.A method is proposed to estimate the ...This work presents a mapping and tracking system based on images to enable a small Unmanned Aerial Vehicle(UAV)to accurately navigate in indoor and GPS-denied outdoor environments.A method is proposed to estimate the UAV’s pose(i.e.,the 3D position and orientation of the camera sensor)in real-time using only the on-board RGB camera as the UAV travels through a known 3D environment(i.e.,a 3D CAD model).Linear features are extracted and automatically matched between images collected by the UAV’s onboard RGB camera and the 3D object model.The matched lines from the 3D model serve as ground control to estimate the camera pose in real-time via line-based space resection.The results demonstrate that the proposed modelbased pose estimation algorithm provides sub-meter positioning accuracies in both indoor and outdoor environments.It is also that shown the proposed method can provide sparse updates to correct the drift from complementary simultaneous localization and mapping(SLAM)-derived pose estimates.展开更多
Facial expression recognition(FER)has numerous applications in computer security,neuroscience,psychology,and engineering.Owing to its non-intrusiveness,it is considered a useful technology for combating crime.However,...Facial expression recognition(FER)has numerous applications in computer security,neuroscience,psychology,and engineering.Owing to its non-intrusiveness,it is considered a useful technology for combating crime.However,FER is plagued with several challenges,the most serious of which is its poor prediction accuracy in severe head poses.The aim of this study,therefore,is to improve the recognition accuracy in severe head poses by proposing a robust 3D head-tracking algorithm based on an ellipsoidal model,advanced ensemble of AdaBoost,and saturated vector machine(SVM).The FER features are tracked from one frame to the next using the ellipsoidal tracking model,and the visible expressive facial key points are extracted using Gabor filters.The ensemble algorithm(Ada-AdaSVM)is then used for feature selection and classification.The proposed technique is evaluated using the Bosphorus,BU-3DFE,MMI,CK^(+),and BP4D-Spontaneous facial expression databases.The overall performance is outstanding.展开更多
基金supported by the Knowledge Innovation Program of Wuhan-Shuguang Project(Grant No.2023010201020443)the School-Level Scientific Research Project Funding Program of Jianghan University(Grant No.2022XKZX33)the Natural Science Foundation of Hubei Province(Grant No.2024AFB466).
文摘The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.
基金co-supported by the National Natural Science Foundation-Outstanding Youth Foundation of China (No. 51622501)the National Natural Science Foundation of China (Nos. 51375075 and 51227004)+1 种基金the Fundamental Research Funds for the Central Universities of Chinathe Science Fund for Creative Research Groups of China (No. 51321004)
文摘The measurement of position and attitude parameters for the isolated target from a highspeed aircraft is a great challenge in the field of wind tunnel simulation technology. This paper proposes a remote-controlled flexible pose measurement system in wind tunnel conditions for the separation of a target from an aircraft. The position and attitude parameters of a moving object are obtained by utilizing a single camera with a focal length and camera orientation that can be changed based on different measurement conditions. Using this proposed system and method, both the flexibility and efficiency of the pose measurement system can be enhanced in wind tunnel conditions to meet the measurement requirements of different objects and experiments, which is also useful for the development of an intelligent position and attitude measurement system. The position and the focal length of the camera also can be controlled remotely during measurements to enlarge both the vertical and horizontal measurement range of this system. Experiments are conducted in the laboratory to measure the position and attitude of moving objects with high flexibility and efficiency, and the measurement precision of the measurement system is also verified through experiments.
基金co-supported by the National Natural Science Foundation of China,China(No.12272404)the Postgraduate Research Innovation Project of Hunan Province of China,China(No.CX20210016).
文摘Due to the portability and anti-interference ability,vision-based shipborne aircraft automatic landing systems have attracted the attention of researchers.In this paper,a Monocular Camera and Laser Range Finder(MC-LRF)-based pose measurement system is designed for shipborne aircraft automatic landing.First,the system represents the target ship using a set of sparse landmarks,and a two-stage model is adopted to detect landmarks on the target ship.The rough 6D pose is measured by solving a Perspective-n-Point problem.Then,once the rough pose is measured,a region-based pose refinement is used to continuously track the 6D pose in the subsequent image sequences.To address the low accuracy of monocular pose measurement in the depth direction,the designed system adopts a laser range finder to obtain an accurate range value.The measured rough pose is iteratively optimized using the accurate range measurement.Experimental results on synthetic and real images show that the system achieves robust and precise pose measurement of the target ship during automatic landing.The measurement means error is within 0.4in rotation,and 0.2%in translation,meeting the requirements for automatic fixed-wing aircraft landing.
文摘An event-triggered moving horizon estimation strategy is proposed for spacecraft pose estimation.The error dual quaternion is used to describe the system state and construct the spacecraft attitude-orbit coupled model.In order to reduce the energy consumption on spacecraft,an event-triggered moving horizon estimator(MHE)is designed for real-time pose estimation with limited communication resources.The model mismatch caused by event-triggered is finally solved by solving the cost function of the min-max optimization problem.The system simulation model is built in Matlab/Simulink,and the spacecraft pose estimation simulation is carried out.The numerical results demonstrate that the designed estimator could ensure the estimation effect and save spacecraft communication and computing resources effectively.
基金Research was supported by the Jiang Xi Provincial Natural Science Foundation of China under Grant 0611005.
文摘Two dynamical system methods are studied for solving linear ill-posed problems with both operator and right-hand nonexact. The methods solve a Cauchy problem for a linear operator equation which possesses a global solution. The limit of the global solution at infinity solves the original linear equation. Moreover, we also present a convergent iterative process for solving the Cauchy problem.
基金This work was supported by NSERC through a Discovery Grant[grant number RGPIN-2015-06211].
文摘This work presents a mapping and tracking system based on images to enable a small Unmanned Aerial Vehicle(UAV)to accurately navigate in indoor and GPS-denied outdoor environments.A method is proposed to estimate the UAV’s pose(i.e.,the 3D position and orientation of the camera sensor)in real-time using only the on-board RGB camera as the UAV travels through a known 3D environment(i.e.,a 3D CAD model).Linear features are extracted and automatically matched between images collected by the UAV’s onboard RGB camera and the 3D object model.The matched lines from the 3D model serve as ground control to estimate the camera pose in real-time via line-based space resection.The results demonstrate that the proposed modelbased pose estimation algorithm provides sub-meter positioning accuracies in both indoor and outdoor environments.It is also that shown the proposed method can provide sparse updates to correct the drift from complementary simultaneous localization and mapping(SLAM)-derived pose estimates.
文摘Facial expression recognition(FER)has numerous applications in computer security,neuroscience,psychology,and engineering.Owing to its non-intrusiveness,it is considered a useful technology for combating crime.However,FER is plagued with several challenges,the most serious of which is its poor prediction accuracy in severe head poses.The aim of this study,therefore,is to improve the recognition accuracy in severe head poses by proposing a robust 3D head-tracking algorithm based on an ellipsoidal model,advanced ensemble of AdaBoost,and saturated vector machine(SVM).The FER features are tracked from one frame to the next using the ellipsoidal tracking model,and the visible expressive facial key points are extracted using Gabor filters.The ensemble algorithm(Ada-AdaSVM)is then used for feature selection and classification.The proposed technique is evaluated using the Bosphorus,BU-3DFE,MMI,CK^(+),and BP4D-Spontaneous facial expression databases.The overall performance is outstanding.
