The significant differences in the physical properties of air and water pose a substantial challenge for the development of hybrid aerial-aquatic vehicle (HAAV), which leading to increased prototype size, heavier thrusters, and reduced efficiency or under-actuation in one of the mediums. This letter introduces “WuKong”, a HAAV with a simple structure, compact size, and high maneuverability. WuKong has a maximum width of only 300 mm in one dimension, with 2.48 thrust-to-weight ratio. Its operational range spans 20 m in the air and 3 m underwater, enabling seamless cross-domain maneuvers. These capabilities are attributed to the use of separate thrusters for aerial and aquatic, in conjunction with the proposed cross-domain hybrid control framework, and the incremental nonlinear dynamic inversion (INDI)-based underwater attitude control law. Through simulations and field experiments, WuKong's cross-domain transition capability and the underwater maneuverability performance are demonstrated. Our development provides a practical solution for HAAV applications and offers a platform for subsequent HAAV collaborative tasks.
{"title":"WuKong: Design, Modeling and Control of a Compact Flexible Hybrid Aerial-Aquatic Vehicle","authors":"Yufan Liu;Cheng Li;Junjie Li;Zemin Lin;Wei Meng;Fumin Zhang","doi":"10.1109/LRA.2024.3521659","DOIUrl":"https://doi.org/10.1109/LRA.2024.3521659","url":null,"abstract":"The significant differences in the physical properties of air and water pose a substantial challenge for the development of hybrid aerial-aquatic vehicle (HAAV), which leading to increased prototype size, heavier thrusters, and reduced efficiency or under-actuation in one of the mediums. This letter introduces “WuKong”, a HAAV with a simple structure, compact size, and high maneuverability. WuKong has a maximum width of only 300 mm in one dimension, with 2.48 thrust-to-weight ratio. Its operational range spans 20 m in the air and 3 m underwater, enabling seamless cross-domain maneuvers. These capabilities are attributed to the use of separate thrusters for aerial and aquatic, in conjunction with the proposed cross-domain hybrid control framework, and the incremental nonlinear dynamic inversion (INDI)-based underwater attitude control law. Through simulations and field experiments, WuKong's cross-domain transition capability and the underwater maneuverability performance are demonstrated. Our development provides a practical solution for HAAV applications and offers a platform for subsequent HAAV collaborative tasks.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 2","pages":"1417-1424"},"PeriodicalIF":4.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142918340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-25DOI: 10.1109/LRA.2024.3522765
Hugo Lefévre;Tomohiro Chaki;Tomohiro Kawakami;Arnaud Tanguy;Takahide Yoshiike;Abderrahmane Kheddar
Standing and sitting are basic tasks that become increasingly difficult with age or frailty. Assisting these movements using humanoid robots is a complex challenge, particularly in determining where and how much force the robot should apply to effectively support the human's dynamic motions. In this letter, we propose a method to compute assistive forces directly from the human's dynamic balance, using criteria typically employed in humanoid robots. Specifically, we map humanoid dynamic balance metrics onto human motion to calculate the forces required to stabilize the human's current posture. These forces are then applied at the appropriate locations on the human body by the humanoid. Our approach combines the variable height 3D divergent component of motion with gravito-inertial wrench cones to define a 3D balance region. Using centroidal feedback, we compute the required assistance force to maintain balance and distribute the resulting wrenches across the human's body using a humanoid robot dynamically balanced according to the same criteria. We demonstrate the effectiveness of this framework through both simulations and experiments, where a humanoid assists a person in sit-to-stand and stand-to-sit motions, with the person wearing an age-simulation suit to emulate frailty.
{"title":"Humanoid-Human Sit-to-Stand-to-Sit Assistance","authors":"Hugo Lefévre;Tomohiro Chaki;Tomohiro Kawakami;Arnaud Tanguy;Takahide Yoshiike;Abderrahmane Kheddar","doi":"10.1109/LRA.2024.3522765","DOIUrl":"https://doi.org/10.1109/LRA.2024.3522765","url":null,"abstract":"Standing and sitting are basic tasks that become increasingly difficult with age or frailty. Assisting these movements using humanoid robots is a complex challenge, particularly in determining where and how much force the robot should apply to effectively support the human's dynamic motions. In this letter, we propose a method to compute assistive forces directly from the human's dynamic balance, using criteria typically employed in humanoid robots. Specifically, we map humanoid dynamic balance metrics onto human motion to calculate the forces required to stabilize the human's current posture. These forces are then applied at the appropriate locations on the human body by the humanoid. Our approach combines the variable height 3D divergent component of motion with gravito-inertial wrench cones to define a 3D balance region. Using centroidal feedback, we compute the required assistance force to maintain balance and distribute the resulting wrenches across the human's body using a humanoid robot dynamically balanced according to the same criteria. We demonstrate the effectiveness of this framework through both simulations and experiments, where a humanoid assists a person in sit-to-stand and stand-to-sit motions, with the person wearing an age-simulation suit to emulate frailty.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 2","pages":"1521-1528"},"PeriodicalIF":4.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-25DOI: 10.1109/LRA.2024.3522786
Satyanarayana G. Manyam;David W. Casbeer;Colin Taylor
We consider a motion planning problem for vehicles with curvature constraints, such as minimum turn radius, and a secondary cost such as resource cost. Traditional motion planning problems address the secondary cost as a soft constraint within the cost function. In the current paper, we take a different approach and treat this as a constraint, separate from the primary objective cost. Specifically, the integrated resource cost along the vehicle's path is constrained to be within a pre-specified limit, which is separate from the main travel cost being optimized. This approach is suitable for applications such as fire fighting, where finding the paths of minimum cost or time is essential while limiting exposure to the high heat areas. To address the resource constraints, we introduce the Hybrid Theta $^*$ (H $boldsymbol{Theta }^*$ ) algorithm. This is an incremental sampling based search algorithm and draws inspiration from labeling algorithms used in resource constrained shortest path problems. We present two versions of the (H $boldsymbol{Theta }^*$ ) algorithm, label-select and focal-select; these variants differs in how labels to be expanded are selected from the processing queue. The proposed algorithms significantly outperform the baseline methods that uses the traditional motion planning algorithms in terms of both the success rate and the solution cost. We validate the algorithms through computational experiments and real-world flight testing with on-board computation.
{"title":"Hybrid Theta$^*$: Motion Planning for Dubins Vehicles With Integral Constraints","authors":"Satyanarayana G. Manyam;David W. Casbeer;Colin Taylor","doi":"10.1109/LRA.2024.3522786","DOIUrl":"https://doi.org/10.1109/LRA.2024.3522786","url":null,"abstract":"We consider a motion planning problem for vehicles with curvature constraints, such as minimum turn radius, and a secondary cost such as resource cost. Traditional motion planning problems address the secondary cost as a soft constraint within the cost function. In the current paper, we take a different approach and treat this as a constraint, separate from the primary objective cost. Specifically, the integrated resource cost along the vehicle's path is constrained to be within a pre-specified limit, which is separate from the main travel cost being optimized. This approach is suitable for applications such as fire fighting, where finding the paths of minimum cost or time is essential while limiting exposure to the high heat areas. To address the resource constraints, we introduce the Hybrid Theta\u0000<inline-formula><tex-math>$^*$</tex-math></inline-formula>\u0000 (H\u0000<inline-formula><tex-math>$boldsymbol{Theta }^*$</tex-math></inline-formula>\u0000) algorithm. This is an incremental sampling based search algorithm and draws inspiration from labeling algorithms used in resource constrained shortest path problems. We present two versions of the (H\u0000<inline-formula><tex-math>$boldsymbol{Theta }^*$</tex-math></inline-formula>\u0000) algorithm, label-select and focal-select; these variants differs in how labels to be expanded are selected from the processing queue. The proposed algorithms significantly outperform the baseline methods that uses the traditional motion planning algorithms in terms of both the success rate and the solution cost. We validate the algorithms through computational experiments and real-world flight testing with on-board computation.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 2","pages":"1497-1504"},"PeriodicalIF":4.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-25DOI: 10.1109/LRA.2024.3522790
Julia Hindel;Daniele Cattaneo;Abhinav Valada
Semantic segmentation models are typically trained on a fixed set of classes, limiting their applicability in open-world scenarios. Class-incremental semantic segmentation aims to update models with emerging new classes while preventing catastrophic forgetting of previously learned ones. However, existing methods impose strict rigidity on old classes, reducing their effectiveness in learning new incremental classes. In this work, we propose Taxonomy-Oriented Poincaré-regularized Incremental-Class Segmentation (TOPICS) that learns feature embeddings in hyperbolic space following explicit taxonomy-tree structures. This supervision provides plasticity for old classes, updating ancestors based on new classes while integrating new classes at fitting positions. Additionally, we maintain implicit class relational constraints on the geometric basis of the Poincaré ball. This ensures that the latent space can continuously adapt to new constraints while maintaining a robust structure to combat catastrophic forgetting. We also establish eight realistic incremental learning protocols for autonomous driving scenarios, where novel classes can originate from known classes or the background. Extensive evaluations of TOPICS on the Cityscapes and Mapillary Vistas 2.0 benchmarks demonstrate that it achieves state-of-the-art performance.
{"title":"Taxonomy-Aware Continual Semantic Segmentation in Hyperbolic Spaces for Open-World Perception","authors":"Julia Hindel;Daniele Cattaneo;Abhinav Valada","doi":"10.1109/LRA.2024.3522790","DOIUrl":"https://doi.org/10.1109/LRA.2024.3522790","url":null,"abstract":"Semantic segmentation models are typically trained on a fixed set of classes, limiting their applicability in open-world scenarios. Class-incremental semantic segmentation aims to update models with emerging new classes while preventing catastrophic forgetting of previously learned ones. However, existing methods impose strict rigidity on old classes, reducing their effectiveness in learning new incremental classes. In this work, we propose Taxonomy-Oriented Poincaré-regularized Incremental-Class Segmentation (TOPICS) that learns feature embeddings in hyperbolic space following explicit taxonomy-tree structures. This supervision provides plasticity for old classes, updating ancestors based on new classes while integrating new classes at fitting positions. Additionally, we maintain implicit class relational constraints on the geometric basis of the Poincaré ball. This ensures that the latent space can continuously adapt to new constraints while maintaining a robust structure to combat catastrophic forgetting. We also establish eight realistic incremental learning protocols for autonomous driving scenarios, where novel classes can originate from known classes or the background. Extensive evaluations of TOPICS on the Cityscapes and Mapillary Vistas 2.0 benchmarks demonstrate that it achieves state-of-the-art performance.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 2","pages":"1904-1911"},"PeriodicalIF":4.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142993078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-25DOI: 10.1109/LRA.2024.3522756
Baiyu Peng;Aude Billard
Planning for diverse real-world robotic tasks necessitates to know and write all constraints. However, instances exist where these constraints are either unknown or challenging to specify accurately. A possible solution is to infer the unknown constraints from expert demonstration. This letter presents a novel two-step Positive-Unlabeled Constraint Learning (PUCL) algorithm to infer a continuous constraint function from demonstrations, without requiring prior knowledge of the true constraint parameterization or environmental model as existing works. We treat all data in demonstrations as positive (feasible) data, and learn a control policy to generate potentially infeasible trajectories, which serve as unlabeled data. The proposed two-step learning framework first identifies reliable infeasible data using a distance metric, and secondly learns a binary feasibility classifier (i.e., constraint function) from the feasible demonstrations and reliable infeasible data. The proposed method is flexible to learn complex-shaped constraint boundary and will not mistakenly classify demonstrations as infeasible as previous methods. The effectiveness of the proposed method is verified in four constrained environments, using a networked policy or a dynamical system policy. It successfully infers the continuous nonlinear constraints and outperforms other baseline methods in terms of constraint accuracy and policy safety.
{"title":"Positive-Unlabeled Constraint Learning for Inferring Nonlinear Continuous Constraints Functions From Expert Demonstrations","authors":"Baiyu Peng;Aude Billard","doi":"10.1109/LRA.2024.3522756","DOIUrl":"https://doi.org/10.1109/LRA.2024.3522756","url":null,"abstract":"Planning for diverse real-world robotic tasks necessitates to know and write all constraints. However, instances exist where these constraints are either unknown or challenging to specify accurately. A possible solution is to infer the unknown constraints from expert demonstration. This letter presents a novel two-step Positive-Unlabeled Constraint Learning (PUCL) algorithm to infer a continuous constraint function from demonstrations, without requiring prior knowledge of the true constraint parameterization or environmental model as existing works. We treat all data in demonstrations as positive (feasible) data, and learn a control policy to generate potentially infeasible trajectories, which serve as unlabeled data. The proposed two-step learning framework first identifies reliable infeasible data using a distance metric, and secondly learns a binary feasibility classifier (i.e., constraint function) from the feasible demonstrations and reliable infeasible data. The proposed method is flexible to learn complex-shaped constraint boundary and will not mistakenly classify demonstrations as infeasible as previous methods. The effectiveness of the proposed method is verified in four constrained environments, using a networked policy or a dynamical system policy. It successfully infers the continuous nonlinear constraints and outperforms other baseline methods in terms of constraint accuracy and policy safety.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 2","pages":"1593-1600"},"PeriodicalIF":4.6,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142940785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-24DOI: 10.1109/LRA.2024.3519239
{"title":"IEEE Robotics and Automation Letters Information for Authors","authors":"","doi":"10.1109/LRA.2024.3519239","DOIUrl":"https://doi.org/10.1109/LRA.2024.3519239","url":null,"abstract":"","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"C4-C4"},"PeriodicalIF":4.6,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10813589","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-24DOI: 10.1109/LRA.2024.3519237
{"title":"IEEE Robotics and Automation Society Information","authors":"","doi":"10.1109/LRA.2024.3519237","DOIUrl":"https://doi.org/10.1109/LRA.2024.3519237","url":null,"abstract":"","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"C3-C3"},"PeriodicalIF":4.6,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10813592","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-24DOI: 10.1109/LRA.2024.3521682
Jayant Unde;Jacinto Colan;Yasuhisa Hasegawa
This letter introduces a novel linear actuator with a high extension ratio, achieved through a unique planar transforming linkage mechanism (TLM) that serves as an articulated lead screw. This mechanism forms a rigid beam when extended and compactly coils when not in use, eliminating the need for an interlocking mechanism and thereby enhancing durability and reducing maintenance costs. The paper also discusses the comprehensive design of the linear actuator, including the articulated lead screw and driving transformation mechanism, leveraging the kinematic properties of the planar TLM. A proof-of-concept prototype is manufactured and assessed for its load capacity, accuracy, repeatability, and efficiency. Unlike conventional actuators constrained by a lower extension ratio, the proposed actuator's compactness and transverse load resilience make it ideal for space-constrained applications such as medical devices, space robotics, and factory automation. Overall, the proposed linear actuator represents a significant advancement in the field of linear actuators and has the potential to enable a wide array of applications that were previously unfeasible with conventional designs.
{"title":"Novel Articulated Lead Screw Linear Actuator Enabled by Transforming Linkage Mechanism","authors":"Jayant Unde;Jacinto Colan;Yasuhisa Hasegawa","doi":"10.1109/LRA.2024.3521682","DOIUrl":"https://doi.org/10.1109/LRA.2024.3521682","url":null,"abstract":"This letter introduces a novel linear actuator with a high extension ratio, achieved through a unique planar transforming linkage mechanism (TLM) that serves as an articulated lead screw. This mechanism forms a rigid beam when extended and compactly coils when not in use, eliminating the need for an interlocking mechanism and thereby enhancing durability and reducing maintenance costs. The paper also discusses the comprehensive design of the linear actuator, including the articulated lead screw and driving transformation mechanism, leveraging the kinematic properties of the planar TLM. A proof-of-concept prototype is manufactured and assessed for its load capacity, accuracy, repeatability, and efficiency. Unlike conventional actuators constrained by a lower extension ratio, the proposed actuator's compactness and transverse load resilience make it ideal for space-constrained applications such as medical devices, space robotics, and factory automation. Overall, the proposed linear actuator represents a significant advancement in the field of linear actuators and has the potential to enable a wide array of applications that were previously unfeasible with conventional designs.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 2","pages":"1369-1376"},"PeriodicalIF":4.6,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10814080","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-24DOI: 10.1109/LRA.2024.3519235
{"title":"IEEE Robotics and Automation Society Information","authors":"","doi":"10.1109/LRA.2024.3519235","DOIUrl":"https://doi.org/10.1109/LRA.2024.3519235","url":null,"abstract":"","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"C2-C2"},"PeriodicalIF":4.6,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10813587","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142880376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-23DOI: 10.1109/LRA.2024.3520922
Hyeonje Cha;Inho Lee;Jungwon Seo
This study introduces a robotic high-speed scooping technique, an effective solution for rapidly picking thin objects from a hard support surface. High-speed scooping involves dynamic and impactful manipulation using a two-fingered gripper. One digit dynamically penetrates beneath the object lying on a support surface while the other digit helps form a cage and subsequently secures a firm grip. This entire process is executed within a fractional-second time frame. We develop a theoretical model of manipulation for high-speed scooping and implement it using our custom direct-drive gripper designed for enhanced environment-adaptability. Extensive experiments verify the viability of our high-speed scooping approach.
{"title":"High-Speed Scooping Through Dynamic Manipulation: Model and Practice","authors":"Hyeonje Cha;Inho Lee;Jungwon Seo","doi":"10.1109/LRA.2024.3520922","DOIUrl":"https://doi.org/10.1109/LRA.2024.3520922","url":null,"abstract":"This study introduces a robotic high-speed scooping technique, an effective solution for rapidly picking thin objects from a hard support surface. High-speed scooping involves dynamic and impactful manipulation using a two-fingered gripper. One digit dynamically penetrates beneath the object lying on a support surface while the other digit helps form a cage and subsequently secures a firm grip. This entire process is executed within a fractional-second time frame. We develop a theoretical model of manipulation for high-speed scooping and implement it using our custom direct-drive gripper designed for enhanced environment-adaptability. Extensive experiments verify the viability of our high-speed scooping approach.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 2","pages":"1377-1384"},"PeriodicalIF":4.6,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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