Three-dimensional(3D)tracking of rigid objects plays a very important role in many areas such as augmented reality,computer vision,and robotics.Numerous works have been done to pursue more stable,faster,and more accur...Three-dimensional(3D)tracking of rigid objects plays a very important role in many areas such as augmented reality,computer vision,and robotics.Numerous works have been done to pursue more stable,faster,and more accurate 3D tracking.Among various tracking methods,edge-based 3D tracking has been widely used owing to its many advantages.Furthermore,edge-based methods can be mainly divided into two categories,methods without and those with explicit edges,depending on whether explicit edges need to be extracted.Based on this,representative methods in both categories are introduced,analyzed,and compared in this paper.Finally,some suggestions on the choice of methods in different application scenarios and research directions in the future are given.展开更多
The dynamics of the drying process of polymer solutions are important for the development of coatings and films.In the present work,digital holographic microscopy(DHM)was performed to capture the drying dynamics of po...The dynamics of the drying process of polymer solutions are important for the development of coatings and films.In the present work,digital holographic microscopy(DHM)was performed to capture the drying dynamics of poly(ethylene oxide)(PEO)droplets using a gold nanoparticle tracer,where the heterogeneous flow field in different regions was illustrated.This demonstrates that the gold nanoparticles at either the center or the edge regions of the droplet exhibit anisotropic kinematic behavior.At early stage,Marangoni backflow causes gold nanoparticles to move towards the edge firstly,and the circles back towards the droplet center after arriving the contact line with a sudden increase in z axis for 10.4μm,indicating the scale of the upward-moving microscopic flow vortices.This phenomenon does not occur in water droplets in the absence of polymers.The gold nanoparticles underwent Brownian-like motion at the center of the PEO droplet or water droplet owing to the low perturbation of the flow field.At the late stage of pinning of the PEO droplets,the motion showed multiple reverses in the direction of the gold nanoparticles,indicating the complexity of the flow field.This study enhances the understanding of the drying dynamics of polymer solution droplets and offers valuable insights into the fabrication of surface materials.展开更多
Three-dimensional (3D) human pose tracking has recently attracted more and more attention in the computer vision field. Real-time pose tracking is highly useful in various domains such as video surveillance, somatosen...Three-dimensional (3D) human pose tracking has recently attracted more and more attention in the computer vision field. Real-time pose tracking is highly useful in various domains such as video surveillance, somatosensory games, and human-computer interaction. However, vision-based pose tracking techniques usually raise privacy concerns, making human pose tracking without vision data usage an important problem. Thus, we propose using Radio Frequency Identification (RFID) as a pose tracking technique via a low-cost wearable sensing device. Although our prior work illustrated how deep learning could transfer RFID data into real-time human poses, generalization for different subjects remains challenging. This paper proposes a subject-adaptive technique to address this generalization problem. In the proposed system, termed Cycle-Pose, we leverage a cross-skeleton learning structure to improve the adaptability of the deep learning model to different human skeletons. Moreover, our novel cycle kinematic network is proposed for unpaired RFID and labeled pose data from different subjects. The Cycle-Pose system is implemented and evaluated by comparing its prototype with a traditional RFID pose tracking system. The experimental results demonstrate that Cycle-Pose can achieve lower estimation error and better subject generalization than the traditional system.展开更多
In the majority of the interaction process, the operator often focuses on the tracked 3D hand gesture model at the ＂interaction points＂ in the collision detectionscene, such as ＂grasp＂ and ＂release＂ and objects ...In the majority of the interaction process, the operator often focuses on the tracked 3D hand gesture model at the ＂interaction points＂ in the collision detectionscene, such as ＂grasp＂ and ＂release＂ and objects in the scene, without paying attention to the tracked 3D hand gesture model in the total procedure. Thus in this paper, a visual attention distribution model of operator in the ＂grasp＂, ＂translation＂, ＂release＂ and other basic operation procedures is first studied and a 3D hand gesture tracking algorithm based on this distribution model is proposed. Utilizing the algorithm, in the period with a low degree of visual attention, a pre-stored 3D hand gesture animation can be used to directly visualise a 3D hand gesture model in the interactive scene; in the time period with a high degree of visual attention, an existing ＂frame-by-frame tracking＂ approach can be adopted to obtain a 3D gesture model. The results demonstrate that the proposed method can achieve real-time tracking of 3D hand gestures with an effective improvement on the efficiency, fluency, and availability of 3D hand gesture interaction.展开更多
The 3D object tracking from a monocular RGB image is a challenging task.Although popular color and edgebased methods have been well studied,they are only applicable to certain cases and new solutions to the challenges...The 3D object tracking from a monocular RGB image is a challenging task.Although popular color and edgebased methods have been well studied,they are only applicable to certain cases and new solutions to the challenges in real environment must be developed.In this paper,we propose a robust 3D object tracking method with adaptively weighted local bundles called AWLB tracker to handle more complicated cases.Each bundle represents a local region containing a set of local features.To alleviate the negative effect of the features in low-confidence regions,the bundles are adaptively weighted using a spatially-variant weighting function based on the confidence values of the involved energy terms.Therefore,in each frame,the weights of the energy items in each bundle are adapted to different situations and different regions of the same frame.Experiments show that the proposed method can improve the overall accuracy in challenging cases.We then verify the effectiveness of the proposed confidence-based adaptive weighting method using ablation studies and show that the proposed method overperforms the existing single-feature methods and multi-feature methods without adaptive weighting.展开更多
Center point localization is a major factor affecting the performance of 3D single object tracking.Point clouds themselves are a set of discrete points on the local surface of an object,and there is also a lot of nois...Center point localization is a major factor affecting the performance of 3D single object tracking.Point clouds themselves are a set of discrete points on the local surface of an object,and there is also a lot of noise in the labeling.Therefore,directly regressing the center coordinates is not very reasonable.Existing methods usually use volumetric-based,point-based,and view-based methods,with a relatively single modality.In addition,the sampling strategies commonly used usually result in the loss of object information,and holistic and detailed information is beneficial for object localization.To address these challenges,we propose a novel Multi-view unsupervised center Uncertainty 3D single object Tracker(MUT).MUT models the potential uncertainty of center coordinates localization using an unsupervised manner,allowing the model to learn the true distribution.By projecting point clouds,MUT can obtain multi-view depth map features,realize efficient knowledge transfer from 2D to 3D,and provide another modality information for the tracker.We also propose a former attraction probability sampling strategy that preserves object information.By using both holistic and detailed descriptors of point clouds,the tracker can have a more comprehensive understanding of the tracking environment.Experimental results show that the proposed MUT network outperforms the baseline models on the KITTI dataset by 0.8%and 0.6%in precision and success rate,respectively,and on the NuScenes dataset by 1.4%,and 6.1%in precision and success rate,respectively.The code is made available at https://github.com/abchears/MUT.git.展开更多
We propose an automatic three-dimensionM （3D） pupil tracking backlight system for holographic 3D display system with large image size and full-parallax accommodation effect. The proposed tracking module is applied t...We propose an automatic three-dimensionM （3D） pupil tracking backlight system for holographic 3D display system with large image size and full-parallax accommodation effect. The proposed tracking module is applied to a holographic 3D display system with two sets of directional holographic imaging module composed of 2 × 2 large scale lens array and 22-inch high-resolution liquid crystal display 3D panel. System architecture is described and experimental results are presented.展开更多
Augmented Reality(AR)applications can be used to improve tasks and mitigate errors during facilities operation and maintenance.This article presents an AR system for facility management using a three-dimensional(3D)ob...Augmented Reality(AR)applications can be used to improve tasks and mitigate errors during facilities operation and maintenance.This article presents an AR system for facility management using a three-dimensional(3D)object tracking method.Through spatial mapping,the object of interest,a pipe trap underneath a sink,is tracked and mixed onto the AR visualization.From that,the maintenance steps are transformed into visible and animated instructions.Although some tracking issues related to the component parts were observed,the designed AR application results demonstrated the potential to improve facility management tasks.展开更多
Three-dimensional(3D)panoramic vision system plays a fundamental role in the biological perception of external information,and naturally becomes a key system for embodied intelligence to interact with the outside worl...Three-dimensional(3D)panoramic vision system plays a fundamental role in the biological perception of external information,and naturally becomes a key system for embodied intelligence to interact with the outside world.A binocular vision system with rotating eyeball has long baseline,large volume and weak sensitivity to motion.A compound eye system has small volume,high sensitivity to motion but poor precision.Here,a planar compound eye microsystem for high precision 3D perception is proposed by combining semiconductor manufacturing process and biological compound eye structure.Using a semiconductor planar image sensor as the sensing unit,a space-coded planar sub-eye array is designed and its sub field of view(FOV)is dynamically mapped to the image sensor.It solves the problem that a traditional vision system cannot simultaneously accommodate wide FOV with long focal length and high sensitivity to motion with high resolution.The parallax among different subeyes enables the system to accurately perceive and dynamically track the 3D position of the target in the range of 10 m and within the FOV of 120°in a single compound eye.This system is of great significance in the fields of intelligent robot and intelligent perception.展开更多
3D object tracking based on deep neural networks has a wide range of potential applications,such as autonomous driving and robotics.However,deep neural networks are vulnerable to adversarial examples.Traditionally,adv...3D object tracking based on deep neural networks has a wide range of potential applications,such as autonomous driving and robotics.However,deep neural networks are vulnerable to adversarial examples.Traditionally,adversarial examples are generated by applying perturbations to individual samples,which requires exhaustive calculations for each sample and thereby suffers from low efficiency during malicious attacks.Hence,the universal adversarial perturbation has been introduced,which is sample-agnostic.The universal perturbation is able to make classifiers misclassify most samples.In this paper,a topology-aware universal adversarial attack method against 3D object tracking is proposed,which can lead to predictions of a 3D tracker deviating from the ground truth in most scenarios.Specifically,a novel objective function consisting of a confidence loss,direction loss and distance loss generates an atomic perturbation from a tracking template,and aims to fail a tracking task.Subsequently,a series of atomic perturbations are iteratively aggregated to derive the universal adversarial perturbation.Furthermore,in order to address the characteristic of permutation invariance inherent in the point cloud data,the topology information of the tracking template is employed to guide the generation of the universal perturbation,which imposes correspondences between consecutively generated perturbations.The generated universal perturbation is designed to be aware of the topology of the targeted tracking template during its construction and application,thus leading to superior attack performance.Experiments on the KITTI dataset demonstrate that the performance of 3D object tracking can be significantly degraded by the proposed method.展开更多
Existing solutions for collaborative trajectory planning using multiple UAVs suffer from issues such as low accuracy,instability,and slow convergence.To address the aforementioned issues,this paper introduces a new me...Existing solutions for collaborative trajectory planning using multiple UAVs suffer from issues such as low accuracy,instability,and slow convergence.To address the aforementioned issues,this paper introduces a new method for multiple unmanned aerial vehicle(UAV)3D terrain cooperative trajectory planning based on the cuck0o search golden jackal optimization(CS-GJO)algorithm.A model for single UAV trajectory planning and a model for multi-UAV collaborative trajectory planning have been developed,and the problem of solving the models is restructured into an optimization problem.Building upon the original golden jackal optimization,the use of tent chaotic mapping aids in the generation of the golden jackal's inital population,thereby promoting population diversity.Subsequently,the position update strategy of the cuckoo search algorithm is combined for purpose of update the position information of individual golden jackals,effectively preventing the algorithm from getting stuck in local minima.Finally,the corresponding nonlinear control parameter were developed.The new parameters expedite the decrease in the convergence factor during the pre-exploration stage,resulting in an improved overall search speed of the algorithm.Moreover,they attenuate the decrease in the convergence factor during the post-exploration stage,thereby enhancing the algorithm's global search.The experimental results demonstrate that the CS-GJO algorithm efficiently and accurately accomplishes multi-UAV cooperative trajectory planning in a 3D environment.Compared with other comparative algorithms,the CS-GJO algorithm also has better stability,higher optimization accuracy,and faster convergence speed.展开更多
The rapid improvement in the running speed,transmission efficiency,and power density of miniaturized devices means that multifunctional flexible composites with excellent thermal management capability and high electro...The rapid improvement in the running speed,transmission efficiency,and power density of miniaturized devices means that multifunctional flexible composites with excellent thermal management capability and high electromagnetic interference(EMI)shielding performance are urgently required.Here,inspired by the fibrous pathways of the human nervous system,a“core–sheath”fibers structured strategy was proposed to prepare thermoplastic polyurethane/polydopamine/carbon nanotube(TPU/PDA/CNT)composites film with thermal management capability and EMI shielding performance.Firstly,TPU@PDA@CNT fibers with CNT shell were prepared by a facile polydopamine-assisted coating on electrospun TPU fibers.Subsequently,TPU/PDA/CNT composites with three-dimensional(3D)fibrous CNT“tracks”are obtained by a hot-pressing process,where CNTs distributed on adjacent fibers are compactly contacted.The fabricated TPU/PDA/CNT composites exhibit a high in-plane thermal conductivity(TC)of 9.6 W/(m·K)at low CNT loading of 7.6 wt.%.In addition,it also presents excellent mechanical properties and excellent EMI shielding effectiveness of 48.3 dB as well as multi-source driven thermal management capabilities.Hence,this study provides a simple yet scalable technique to prepare composites with advanced thermal management and EMI shielding performance to develop new-generation wireless communication technologies and portable intelligent electronic devices.展开更多
Real driving scenarios,due to occlusions and disturbances,provide disordered and noisy measurements,which makes the task of multi-object tracking quite challenging.Conventional approach is to find deterministic data a...Real driving scenarios,due to occlusions and disturbances,provide disordered and noisy measurements,which makes the task of multi-object tracking quite challenging.Conventional approach is to find deterministic data association;however,it has unstable performance in high clutter density.This paper proposes a novel probabilistic tracklet-enhanced multiple object tracker(PTMOT),which integrates Poisson multi-Bernoulli mixture(PMBM)filter with confidence of tracklets.The proposed method is able to realize efficient and robust probabilistic association for 3D multi-object tracking(MOT)and improve the PMBM filter’s continuity by smoothing single target hypothesis with global hypothesis.It consists of two key parts.First,the PMBM tracker based on sets of tracklets is implemented to realize probabilistic fusion of disordered measure-ments.Second,the confidence of tracklets is smoothed through a smoothing-while-filtering approach.Extensive MOT tests on nuScenes tracking dataset demonstrate that the proposed method achieves superior performance in different modalities.展开更多
基金Special Program of the Ministry of Industry and Information Technology of China.
文摘Three-dimensional(3D)tracking of rigid objects plays a very important role in many areas such as augmented reality,computer vision,and robotics.Numerous works have been done to pursue more stable,faster,and more accurate 3D tracking.Among various tracking methods,edge-based 3D tracking has been widely used owing to its many advantages.Furthermore,edge-based methods can be mainly divided into two categories,methods without and those with explicit edges,depending on whether explicit edges need to be extracted.Based on this,representative methods in both categories are introduced,analyzed,and compared in this paper.Finally,some suggestions on the choice of methods in different application scenarios and research directions in the future are given.
基金supported by the Key-Area Research and Development Program of Guangdong Province(No.2023B0101200006)Guangdong Basic and Applied Basic Research Foundation(No.2024A1515011926)+1 种基金Fund of Guangdong Provincial Key Laboratory of Luminescence from Molecular Aggregates,Guangzhou 510640,China(South China University of Technology)(No.2023B1212060003)State Key Laboratory of Applied Microbiology Southern China(No.SKLAM008-2022)。
文摘The dynamics of the drying process of polymer solutions are important for the development of coatings and films.In the present work,digital holographic microscopy(DHM)was performed to capture the drying dynamics of poly(ethylene oxide)(PEO)droplets using a gold nanoparticle tracer,where the heterogeneous flow field in different regions was illustrated.This demonstrates that the gold nanoparticles at either the center or the edge regions of the droplet exhibit anisotropic kinematic behavior.At early stage,Marangoni backflow causes gold nanoparticles to move towards the edge firstly,and the circles back towards the droplet center after arriving the contact line with a sudden increase in z axis for 10.4μm,indicating the scale of the upward-moving microscopic flow vortices.This phenomenon does not occur in water droplets in the absence of polymers.The gold nanoparticles underwent Brownian-like motion at the center of the PEO droplet or water droplet owing to the low perturbation of the flow field.At the late stage of pinning of the PEO droplets,the motion showed multiple reverses in the direction of the gold nanoparticles,indicating the complexity of the flow field.This study enhances the understanding of the drying dynamics of polymer solution droplets and offers valuable insights into the fabrication of surface materials.
基金supported in part by the US National Science Foundation(NSF)under Grants ECCS-1923163 and CNS-2107190through the Wireless Engineering Research and Education Center at Auburn University.
文摘Three-dimensional (3D) human pose tracking has recently attracted more and more attention in the computer vision field. Real-time pose tracking is highly useful in various domains such as video surveillance, somatosensory games, and human-computer interaction. However, vision-based pose tracking techniques usually raise privacy concerns, making human pose tracking without vision data usage an important problem. Thus, we propose using Radio Frequency Identification (RFID) as a pose tracking technique via a low-cost wearable sensing device. Although our prior work illustrated how deep learning could transfer RFID data into real-time human poses, generalization for different subjects remains challenging. This paper proposes a subject-adaptive technique to address this generalization problem. In the proposed system, termed Cycle-Pose, we leverage a cross-skeleton learning structure to improve the adaptability of the deep learning model to different human skeletons. Moreover, our novel cycle kinematic network is proposed for unpaired RFID and labeled pose data from different subjects. The Cycle-Pose system is implemented and evaluated by comparing its prototype with a traditional RFID pose tracking system. The experimental results demonstrate that Cycle-Pose can achieve lower estimation error and better subject generalization than the traditional system.
基金Supported by the National Natural Science Foundation of China(61472163)the National Key Research&Development Plan of China(2016YFB1001403)the Science and Technology Project of Shandong Province(2015GGX101025)
文摘In the majority of the interaction process, the operator often focuses on the tracked 3D hand gesture model at the ＂interaction points＂ in the collision detectionscene, such as ＂grasp＂ and ＂release＂ and objects in the scene, without paying attention to the tracked 3D hand gesture model in the total procedure. Thus in this paper, a visual attention distribution model of operator in the ＂grasp＂, ＂translation＂, ＂release＂ and other basic operation procedures is first studied and a 3D hand gesture tracking algorithm based on this distribution model is proposed. Utilizing the algorithm, in the period with a low degree of visual attention, a pre-stored 3D hand gesture animation can be used to directly visualise a 3D hand gesture model in the interactive scene; in the time period with a high degree of visual attention, an existing ＂frame-by-frame tracking＂ approach can be adopted to obtain a 3D gesture model. The results demonstrate that the proposed method can achieve real-time tracking of 3D hand gestures with an effective improvement on the efficiency, fluency, and availability of 3D hand gesture interaction.
基金supported by Zhejiang Lab under Grant No.2020NB0AB02the Industrial Internet Innovation and Development Project in 2019 of China。
文摘The 3D object tracking from a monocular RGB image is a challenging task.Although popular color and edgebased methods have been well studied,they are only applicable to certain cases and new solutions to the challenges in real environment must be developed.In this paper,we propose a robust 3D object tracking method with adaptively weighted local bundles called AWLB tracker to handle more complicated cases.Each bundle represents a local region containing a set of local features.To alleviate the negative effect of the features in low-confidence regions,the bundles are adaptively weighted using a spatially-variant weighting function based on the confidence values of the involved energy terms.Therefore,in each frame,the weights of the energy items in each bundle are adapted to different situations and different regions of the same frame.Experiments show that the proposed method can improve the overall accuracy in challenging cases.We then verify the effectiveness of the proposed confidence-based adaptive weighting method using ablation studies and show that the proposed method overperforms the existing single-feature methods and multi-feature methods without adaptive weighting.
文摘Center point localization is a major factor affecting the performance of 3D single object tracking.Point clouds themselves are a set of discrete points on the local surface of an object,and there is also a lot of noise in the labeling.Therefore,directly regressing the center coordinates is not very reasonable.Existing methods usually use volumetric-based,point-based,and view-based methods,with a relatively single modality.In addition,the sampling strategies commonly used usually result in the loss of object information,and holistic and detailed information is beneficial for object localization.To address these challenges,we propose a novel Multi-view unsupervised center Uncertainty 3D single object Tracker(MUT).MUT models the potential uncertainty of center coordinates localization using an unsupervised manner,allowing the model to learn the true distribution.By projecting point clouds,MUT can obtain multi-view depth map features,realize efficient knowledge transfer from 2D to 3D,and provide another modality information for the tracker.We also propose a former attraction probability sampling strategy that preserves object information.By using both holistic and detailed descriptors of point clouds,the tracker can have a more comprehensive understanding of the tracking environment.Experimental results show that the proposed MUT network outperforms the baseline models on the KITTI dataset by 0.8%and 0.6%in precision and success rate,respectively,and on the NuScenes dataset by 1.4%,and 6.1%in precision and success rate,respectively.The code is made available at https://github.com/abchears/MUT.git.
基金supported by Giga KOREA project(GK13D0100,Development of Telecommunications Terminal with Digital Holographic Table-top Display)
文摘We propose an automatic three-dimensionM （3D） pupil tracking backlight system for holographic 3D display system with large image size and full-parallax accommodation effect. The proposed tracking module is applied to a holographic 3D display system with two sets of directional holographic imaging module composed of 2 × 2 large scale lens array and 22-inch high-resolution liquid crystal display 3D panel. System architecture is described and experimental results are presented.
文摘Augmented Reality(AR)applications can be used to improve tasks and mitigate errors during facilities operation and maintenance.This article presents an AR system for facility management using a three-dimensional(3D)object tracking method.Through spatial mapping,the object of interest,a pipe trap underneath a sink,is tracked and mixed onto the AR visualization.From that,the maintenance steps are transformed into visible and animated instructions.Although some tracking issues related to the component parts were observed,the designed AR application results demonstrated the potential to improve facility management tasks.
基金supported by the National Key Research and Development Program of China(2023YFB3906300).
文摘Three-dimensional(3D)panoramic vision system plays a fundamental role in the biological perception of external information,and naturally becomes a key system for embodied intelligence to interact with the outside world.A binocular vision system with rotating eyeball has long baseline,large volume and weak sensitivity to motion.A compound eye system has small volume,high sensitivity to motion but poor precision.Here,a planar compound eye microsystem for high precision 3D perception is proposed by combining semiconductor manufacturing process and biological compound eye structure.Using a semiconductor planar image sensor as the sensing unit,a space-coded planar sub-eye array is designed and its sub field of view(FOV)is dynamically mapped to the image sensor.It solves the problem that a traditional vision system cannot simultaneously accommodate wide FOV with long focal length and high sensitivity to motion with high resolution.The parallax among different subeyes enables the system to accurately perceive and dynamically track the 3D position of the target in the range of 10 m and within the FOV of 120°in a single compound eye.This system is of great significance in the fields of intelligent robot and intelligent perception.
基金supported by the National Natural Science Foundation of China(No.62072076)the Sichuan Provincial Research Plan Project(No.2022ZDZX0005).
文摘3D object tracking based on deep neural networks has a wide range of potential applications,such as autonomous driving and robotics.However,deep neural networks are vulnerable to adversarial examples.Traditionally,adversarial examples are generated by applying perturbations to individual samples,which requires exhaustive calculations for each sample and thereby suffers from low efficiency during malicious attacks.Hence,the universal adversarial perturbation has been introduced,which is sample-agnostic.The universal perturbation is able to make classifiers misclassify most samples.In this paper,a topology-aware universal adversarial attack method against 3D object tracking is proposed,which can lead to predictions of a 3D tracker deviating from the ground truth in most scenarios.Specifically,a novel objective function consisting of a confidence loss,direction loss and distance loss generates an atomic perturbation from a tracking template,and aims to fail a tracking task.Subsequently,a series of atomic perturbations are iteratively aggregated to derive the universal adversarial perturbation.Furthermore,in order to address the characteristic of permutation invariance inherent in the point cloud data,the topology information of the tracking template is employed to guide the generation of the universal perturbation,which imposes correspondences between consecutively generated perturbations.The generated universal perturbation is designed to be aware of the topology of the targeted tracking template during its construction and application,thus leading to superior attack performance.Experiments on the KITTI dataset demonstrate that the performance of 3D object tracking can be significantly degraded by the proposed method.
基金supported by the Key Research and Development Program of Henan Province (No.241111222900)Natural Science Foundation of Henan (No.242300421716)+2 种基金Key Science and Technology Program of Henan Province (Nos.242102220044 and 242102210034)National Natural Science Foundation of China (No.62103379)Maker Space Incubation Project (No.2023ZCKJ102).
文摘Existing solutions for collaborative trajectory planning using multiple UAVs suffer from issues such as low accuracy,instability,and slow convergence.To address the aforementioned issues,this paper introduces a new method for multiple unmanned aerial vehicle(UAV)3D terrain cooperative trajectory planning based on the cuck0o search golden jackal optimization(CS-GJO)algorithm.A model for single UAV trajectory planning and a model for multi-UAV collaborative trajectory planning have been developed,and the problem of solving the models is restructured into an optimization problem.Building upon the original golden jackal optimization,the use of tent chaotic mapping aids in the generation of the golden jackal's inital population,thereby promoting population diversity.Subsequently,the position update strategy of the cuckoo search algorithm is combined for purpose of update the position information of individual golden jackals,effectively preventing the algorithm from getting stuck in local minima.Finally,the corresponding nonlinear control parameter were developed.The new parameters expedite the decrease in the convergence factor during the pre-exploration stage,resulting in an improved overall search speed of the algorithm.Moreover,they attenuate the decrease in the convergence factor during the post-exploration stage,thereby enhancing the algorithm's global search.The experimental results demonstrate that the CS-GJO algorithm efficiently and accurately accomplishes multi-UAV cooperative trajectory planning in a 3D environment.Compared with other comparative algorithms,the CS-GJO algorithm also has better stability,higher optimization accuracy,and faster convergence speed.
基金supported by the National Natural Science Foundation of China(Nos.21704096,51703217,and 12072325)the Natural Science Foundation of Henan Province(No.20A430028).
文摘The rapid improvement in the running speed,transmission efficiency,and power density of miniaturized devices means that multifunctional flexible composites with excellent thermal management capability and high electromagnetic interference(EMI)shielding performance are urgently required.Here,inspired by the fibrous pathways of the human nervous system,a“core–sheath”fibers structured strategy was proposed to prepare thermoplastic polyurethane/polydopamine/carbon nanotube(TPU/PDA/CNT)composites film with thermal management capability and EMI shielding performance.Firstly,TPU@PDA@CNT fibers with CNT shell were prepared by a facile polydopamine-assisted coating on electrospun TPU fibers.Subsequently,TPU/PDA/CNT composites with three-dimensional(3D)fibrous CNT“tracks”are obtained by a hot-pressing process,where CNTs distributed on adjacent fibers are compactly contacted.The fabricated TPU/PDA/CNT composites exhibit a high in-plane thermal conductivity(TC)of 9.6 W/(m·K)at low CNT loading of 7.6 wt.%.In addition,it also presents excellent mechanical properties and excellent EMI shielding effectiveness of 48.3 dB as well as multi-source driven thermal management capabilities.Hence,this study provides a simple yet scalable technique to prepare composites with advanced thermal management and EMI shielding performance to develop new-generation wireless communication technologies and portable intelligent electronic devices.
基金supported by International Science and Technology Cooperation Program of China(2019YFE0100200)in part by National Natural Science Foundation of China(61903220)National Natural Science Foundation of China(U1864203).
文摘Real driving scenarios,due to occlusions and disturbances,provide disordered and noisy measurements,which makes the task of multi-object tracking quite challenging.Conventional approach is to find deterministic data association;however,it has unstable performance in high clutter density.This paper proposes a novel probabilistic tracklet-enhanced multiple object tracker(PTMOT),which integrates Poisson multi-Bernoulli mixture(PMBM)filter with confidence of tracklets.The proposed method is able to realize efficient and robust probabilistic association for 3D multi-object tracking(MOT)and improve the PMBM filter’s continuity by smoothing single target hypothesis with global hypothesis.It consists of two key parts.First,the PMBM tracker based on sets of tracklets is implemented to realize probabilistic fusion of disordered measure-ments.Second,the confidence of tracklets is smoothed through a smoothing-while-filtering approach.Extensive MOT tests on nuScenes tracking dataset demonstrate that the proposed method achieves superior performance in different modalities.
