The lack of autonomous aerial refueling capabilities is one of the greatest limitations of unmanned aerial vehicles. This paper discusses the vision-based estimation of the relative pose of a tanker and unmanned aeria...The lack of autonomous aerial refueling capabilities is one of the greatest limitations of unmanned aerial vehicles. This paper discusses the vision-based estimation of the relative pose of a tanker and unmanned aerial vehicle, which is a key issue in autonomous aerial refueling. The main task of this paper is to study the relative pose estimation for a tanker and unmanned aerial vehicle in the phase of commencing refueling and during refueling. The employed algorithm includes the initialization of the orientation parameters and an orthogonal iteration algorithm to estimate the optimal solution of rotation matrix and translation vector. In simulation experiments, because of the small variation in the rotation angle in aerial refueling, the method in which the initial rotation matrix is the identity matrix is found to be the most stable and accurate among methods. Finally, the paper discusses the effects of the number and configuration of feature points on the accuracy of the estimation results when using this method.展开更多
Human pose estimation(HPE)is a procedure for determining the structure of the body pose and it is considered a challenging issue in the computer vision(CV)communities.HPE finds its applications in several fields namel...Human pose estimation(HPE)is a procedure for determining the structure of the body pose and it is considered a challenging issue in the computer vision(CV)communities.HPE finds its applications in several fields namely activity recognition and human-computer interface.Despite the benefits of HPE,it is still a challenging process due to the variations in visual appearances,lighting,occlusions,dimensionality,etc.To resolve these issues,this paper presents a squirrel search optimization with a deep convolutional neural network for HPE(SSDCNN-HPE)technique.The major intention of the SSDCNN-HPE technique is to identify the human pose accurately and efficiently.Primarily,the video frame conversion process is performed and pre-processing takes place via bilateral filtering-based noise removal process.Then,the EfficientNet model is applied to identify the body points of a person with no problem constraints.Besides,the hyperparameter tuning of the EfficientNet model takes place by the use of the squirrel search algorithm(SSA).In the final stage,the multiclass support vector machine(M-SVM)technique was utilized for the identification and classification of human poses.The design of bilateral filtering followed by SSA based EfficientNetmodel for HPE depicts the novelty of the work.To demonstrate the enhanced outcomes of the SSDCNN-HPE approach,a series of simulations are executed.The experimental results reported the betterment of the SSDCNN-HPE system over the recent existing techniques in terms of different measures.展开更多
This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and position...This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and positions,while the followers can measure the relative bearings or(angular and linear)velocities in their unknown local coordinate frames.For the orientation estimation,the local relative bearings are used to obtain the relative orientations among the agents,based on which a distributed orientation estimation algorithm is proposed for each follower to estimate its orientation.For the position estimation,the local relative bearings are used to obtain the position constraints among the agents,and a distributed position estimation algorithm is proposed for each follower to estimate its position by solving its position constraints.Both the orientation and position estimation errors converge to zero asymptotically.A simulation example is given to verify the theoretical results.展开更多
Purpose–On-orbitservice technologyis one of the key technologies of space manipulation activities such as spacecraft life extension,fault spacecraft capture,on-orbit debris removal and so on.It is known that the fail...Purpose–On-orbitservice technologyis one of the key technologies of space manipulation activities such as spacecraft life extension,fault spacecraft capture,on-orbit debris removal and so on.It is known that the failure satellites,space debris and enemy spacecrafts in space are almost all non-cooperative targets.Relatively accurate pose estimation is critical to spatial operations,but also a recognized technical difficulty because of the undefined prior information of non-cooperative targets.With the rapid development of laser radar,the application of laser scanning equipment is increasing in the measurement of non-cooperative targets.It is necessary to research a new pose estimation method for non-cooperative targets based on 3D point cloud.The paper aims to discuss these issues.Design/methodology/approach–In this paper,a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose(position and attitude)of the spatial non-cooperative target.First,we need to preprocess the obtained point cloud to reduce noise and improve the quality of data.Second,according to the features of the satellite,a recognition system used for non-cooperative measurement is designed.The components which are common in the configuration of satellite are chosen as the recognized object.Finally,based on the identified object,the ICP algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose estimation.Findings–The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching points.The recognition of components on non-cooperative spacecraft directly contributes to the space docking,on-orbit capture and relative navigation.Research limitations/implications–Limited to the measurement distance of the laser radar,this paper considers the pose estimation for non-cooperative spacecraft in the close range.Practical implications–The pose estimation method for non-cooperative spacecraft in this paper is mainly applied to close proximity space operations such as final rendezvous phase of spacecraft or ultra-close approaching phase of target capture.Thesystem can recognizecomponents needed to be captureand provide the relative pose of non-cooperative spacecraft.The method in this paper is more robust compared with the traditional single component recognition method and overall matching method when scanning of laser radar is not complete or the components are blocked.Originality/value–This paper introduces a new pose estimation method for non-cooperative spacecraft based on point cloud.The experimental results show that the proposed method can effectively identify the features of non-cooperative targets and track their position and attitude.The method is robust to the noise and greatly improves the speed of pose estimation while guarantee the accuracy.展开更多
变电站室内无人机巡检可有效降低人工巡检作业强度。由于飞行精度要求高,搭载能力有限,仅依靠无人机搭载摄像头与惯性测量单元(inertial measurement unit, IMU)数据融合确定位姿无法满足精度要求,为此,提出基于变电站室内已有固定摄像...变电站室内无人机巡检可有效降低人工巡检作业强度。由于飞行精度要求高,搭载能力有限,仅依靠无人机搭载摄像头与惯性测量单元(inertial measurement unit, IMU)数据融合确定位姿无法满足精度要求,为此,提出基于变电站室内已有固定摄像头的泛在物联的多视觉-惯导融合框架,针对室内光线情况对无人机摄像头图像进行强化,并与IMU数据结合得到初步的无人机位置数据。进一步通过在无人机上布设二维码(quick response code,QR码),应用改进后的PnP(perspective-n-point)算法优化无人机位姿数据。飞行结束后在无人机机巢对IMU的累计误差进行校验。实验证明:该方法布设与维护的工作量小,相较仅依靠搭载摄像头与IMU数据融合算法,飞行精度有较大提高,可满足变电站内无人机巡检作业的需要。展开更多
基金National Natural Science Foundation of China （51075207） Startup Foundation for Introduced Talents of Nanjing University of Aeronautics and Astronautics （1007-YAH10047）
文摘The lack of autonomous aerial refueling capabilities is one of the greatest limitations of unmanned aerial vehicles. This paper discusses the vision-based estimation of the relative pose of a tanker and unmanned aerial vehicle, which is a key issue in autonomous aerial refueling. The main task of this paper is to study the relative pose estimation for a tanker and unmanned aerial vehicle in the phase of commencing refueling and during refueling. The employed algorithm includes the initialization of the orientation parameters and an orthogonal iteration algorithm to estimate the optimal solution of rotation matrix and translation vector. In simulation experiments, because of the small variation in the rotation angle in aerial refueling, the method in which the initial rotation matrix is the identity matrix is found to be the most stable and accurate among methods. Finally, the paper discusses the effects of the number and configuration of feature points on the accuracy of the estimation results when using this method.
文摘Human pose estimation(HPE)is a procedure for determining the structure of the body pose and it is considered a challenging issue in the computer vision(CV)communities.HPE finds its applications in several fields namely activity recognition and human-computer interface.Despite the benefits of HPE,it is still a challenging process due to the variations in visual appearances,lighting,occlusions,dimensionality,etc.To resolve these issues,this paper presents a squirrel search optimization with a deep convolutional neural network for HPE(SSDCNN-HPE)technique.The major intention of the SSDCNN-HPE technique is to identify the human pose accurately and efficiently.Primarily,the video frame conversion process is performed and pre-processing takes place via bilateral filtering-based noise removal process.Then,the EfficientNet model is applied to identify the body points of a person with no problem constraints.Besides,the hyperparameter tuning of the EfficientNet model takes place by the use of the squirrel search algorithm(SSA).In the final stage,the multiclass support vector machine(M-SVM)technique was utilized for the identification and classification of human poses.The design of bilateral filtering followed by SSA based EfficientNetmodel for HPE depicts the novelty of the work.To demonstrate the enhanced outcomes of the SSDCNN-HPE approach,a series of simulations are executed.The experimental results reported the betterment of the SSDCNN-HPE system over the recent existing techniques in terms of different measures.
基金supported by Nanyang Technological University,Singapore under the Wallenberg-NTU Presidential Postdoctoral Fellowship and the Natural Science Foundation in Heilongjiang Province,China(YQ2022F003).
文摘This article studies distributed pose(orientation and position)estimation of leader–follower multi-agent systems over𝜅-layer graphs in 2-D plane.Only the leaders have access to their orientations and positions,while the followers can measure the relative bearings or(angular and linear)velocities in their unknown local coordinate frames.For the orientation estimation,the local relative bearings are used to obtain the relative orientations among the agents,based on which a distributed orientation estimation algorithm is proposed for each follower to estimate its orientation.For the position estimation,the local relative bearings are used to obtain the position constraints among the agents,and a distributed position estimation algorithm is proposed for each follower to estimate its position by solving its position constraints.Both the orientation and position estimation errors converge to zero asymptotically.A simulation example is given to verify the theoretical results.
文摘Purpose–On-orbitservice technologyis one of the key technologies of space manipulation activities such as spacecraft life extension,fault spacecraft capture,on-orbit debris removal and so on.It is known that the failure satellites,space debris and enemy spacecrafts in space are almost all non-cooperative targets.Relatively accurate pose estimation is critical to spatial operations,but also a recognized technical difficulty because of the undefined prior information of non-cooperative targets.With the rapid development of laser radar,the application of laser scanning equipment is increasing in the measurement of non-cooperative targets.It is necessary to research a new pose estimation method for non-cooperative targets based on 3D point cloud.The paper aims to discuss these issues.Design/methodology/approach–In this paper,a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose(position and attitude)of the spatial non-cooperative target.First,we need to preprocess the obtained point cloud to reduce noise and improve the quality of data.Second,according to the features of the satellite,a recognition system used for non-cooperative measurement is designed.The components which are common in the configuration of satellite are chosen as the recognized object.Finally,based on the identified object,the ICP algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose estimation.Findings–The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching points.The recognition of components on non-cooperative spacecraft directly contributes to the space docking,on-orbit capture and relative navigation.Research limitations/implications–Limited to the measurement distance of the laser radar,this paper considers the pose estimation for non-cooperative spacecraft in the close range.Practical implications–The pose estimation method for non-cooperative spacecraft in this paper is mainly applied to close proximity space operations such as final rendezvous phase of spacecraft or ultra-close approaching phase of target capture.Thesystem can recognizecomponents needed to be captureand provide the relative pose of non-cooperative spacecraft.The method in this paper is more robust compared with the traditional single component recognition method and overall matching method when scanning of laser radar is not complete or the components are blocked.Originality/value–This paper introduces a new pose estimation method for non-cooperative spacecraft based on point cloud.The experimental results show that the proposed method can effectively identify the features of non-cooperative targets and track their position and attitude.The method is robust to the noise and greatly improves the speed of pose estimation while guarantee the accuracy.
