Pub Date : 2017-09-28DOI: 10.1109/IROS.2017.8202247
Zhi Yan, T. Duckett, N. Bellotto
Human detection and tracking are essential aspects to be considered in service robotics, as the robot often shares its workspace and interacts closely with humans. This paper presents an online learning framework for human classification in 3D LiDAR scans, taking advantage of robust multi-target tracking to avoid the need for data annotation by a human expert. The system learns iteratively by retraining a classifier online with the samples collected by the robot over time. A novel aspect of our approach is that errors in training data can be corrected using the information provided by the 3D LiDAR-based tracking. In order to do this, an efficient 3D cluster detector of potential human targets has been implemented. We evaluate the framework using a new 3D LiDAR dataset of people moving in a large indoor public space, which is made available to the research community. The experiments analyse the real-time performance of the cluster detector and show that our online learned human classifier matches and in some cases outperforms its offline version.
{"title":"Online learning for human classification in 3D LiDAR-based tracking","authors":"Zhi Yan, T. Duckett, N. Bellotto","doi":"10.1109/IROS.2017.8202247","DOIUrl":"https://doi.org/10.1109/IROS.2017.8202247","url":null,"abstract":"Human detection and tracking are essential aspects to be considered in service robotics, as the robot often shares its workspace and interacts closely with humans. This paper presents an online learning framework for human classification in 3D LiDAR scans, taking advantage of robust multi-target tracking to avoid the need for data annotation by a human expert. The system learns iteratively by retraining a classifier online with the samples collected by the robot over time. A novel aspect of our approach is that errors in training data can be corrected using the information provided by the 3D LiDAR-based tracking. In order to do this, an efficient 3D cluster detector of potential human targets has been implemented. We evaluate the framework using a new 3D LiDAR dataset of people moving in a large indoor public space, which is made available to the research community. The experiments analyse the real-time performance of the cluster detector and show that our online learned human classifier matches and in some cases outperforms its offline version.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"52 1","pages":"864-871"},"PeriodicalIF":0.0,"publicationDate":"2017-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78349967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-26DOI: 10.1109/IROS.2017.8206116
Peter Lehner, A. Albu-Schäffer
We present repetition sampling, a new adaptive strategy for sampling based planning, which extracts information from previous solutions to focus the search for a similar task on relevant configuration space. We show how to generate distributions for repetition sampling by learning Gaussian Mixture Models from prior solutions. We present how to bias a sampling based planner with the learned distribution to generate new paths for similar tasks. We illustrate our method in a simple maze which explains the generation of the distribution and how repetition sampling can generalize over different environments. We show how to apply repetition sampling to similar constrained manipulation tasks and present our results including significant speedup in execution time when compared to uniform sampling.
{"title":"Repetition sampling for efficiently planning similar constrained manipulation tasks","authors":"Peter Lehner, A. Albu-Schäffer","doi":"10.1109/IROS.2017.8206116","DOIUrl":"https://doi.org/10.1109/IROS.2017.8206116","url":null,"abstract":"We present repetition sampling, a new adaptive strategy for sampling based planning, which extracts information from previous solutions to focus the search for a similar task on relevant configuration space. We show how to generate distributions for repetition sampling by learning Gaussian Mixture Models from prior solutions. We present how to bias a sampling based planner with the learned distribution to generate new paths for similar tasks. We illustrate our method in a simple maze which explains the generation of the distribution and how repetition sampling can generalize over different environments. We show how to apply repetition sampling to similar constrained manipulation tasks and present our results including significant speedup in execution time when compared to uniform sampling.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"39 1","pages":"2851-2856"},"PeriodicalIF":0.0,"publicationDate":"2017-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75129194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-26DOI: 10.1109/IROS.2017.8206181
Youngji Kim, Ayoung Kim
Researchers in the simultaneous localization and mapping (SLAM) community have taken for granted that uncertainty associated with the robot pose increases until the loop is closed. However, recently identified by [1], the monotonicity of uncertainty during exploration breaks when the robot returns to the initial position. In this paper, we propose a hypothesis that the monotonicity of pose uncertainty is preserved when the uncertainty is propagated on Lie groups rather than on Euclidean vector space. After deriving covariance propagated over Lie groups and Euclidean vector space, respectively, the monotonicity of uncertainty in each case is thoroughly investigated. Experiments with simulated and real-world scenarios on dead-reckoning validate our hypothesis on the monotonicity of uncertainty.
{"title":"On the uncertainty propagation: Why uncertainty on lie groups preserves monotonicity?","authors":"Youngji Kim, Ayoung Kim","doi":"10.1109/IROS.2017.8206181","DOIUrl":"https://doi.org/10.1109/IROS.2017.8206181","url":null,"abstract":"Researchers in the simultaneous localization and mapping (SLAM) community have taken for granted that uncertainty associated with the robot pose increases until the loop is closed. However, recently identified by [1], the monotonicity of uncertainty during exploration breaks when the robot returns to the initial position. In this paper, we propose a hypothesis that the monotonicity of pose uncertainty is preserved when the uncertainty is propagated on Lie groups rather than on Euclidean vector space. After deriving covariance propagated over Lie groups and Euclidean vector space, respectively, the monotonicity of uncertainty in each case is thoroughly investigated. Experiments with simulated and real-world scenarios on dead-reckoning validate our hypothesis on the monotonicity of uncertainty.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"37 1","pages":"3425-3432"},"PeriodicalIF":0.0,"publicationDate":"2017-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81940592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-24DOI: 10.1109/IROS.2017.8205966
Achkan Salehi, V. Gay-Bellile, S. Bourgeois, N. Allezard, F. Chausse
Constrained key-frame based local bundle adjustment is at the core of many recent systems that address the problem of large-scale, georeferenced SLAM based on a monocular camera and on data from inexpensive sensors and/or databases. The majority of these methods, however, impose constraints that result from proprioceptive sensors (e.g. IMUs, GPS, Odometry) while ignoring the possibility of explicitly constraining the structure (e.g. point cloud) resulting from the reconstruction process. Moreover, research on on-line interactions between SLAM and deep learning methods remains scarce, and as a result, few SLAM systems take advantage of deep architectures. We explore both these areas in this work: we use a fast deep neural network to infer semantic and structural information about the environment, and using a Bayesian framework, inject the results into a bundle adjustment process that constrains the 3d point cloud to texture-less 3d building models.
{"title":"Large-scale, drift-free SLAM using highly robustified building model constraints","authors":"Achkan Salehi, V. Gay-Bellile, S. Bourgeois, N. Allezard, F. Chausse","doi":"10.1109/IROS.2017.8205966","DOIUrl":"https://doi.org/10.1109/IROS.2017.8205966","url":null,"abstract":"Constrained key-frame based local bundle adjustment is at the core of many recent systems that address the problem of large-scale, georeferenced SLAM based on a monocular camera and on data from inexpensive sensors and/or databases. The majority of these methods, however, impose constraints that result from proprioceptive sensors (e.g. IMUs, GPS, Odometry) while ignoring the possibility of explicitly constraining the structure (e.g. point cloud) resulting from the reconstruction process. Moreover, research on on-line interactions between SLAM and deep learning methods remains scarce, and as a result, few SLAM systems take advantage of deep architectures. We explore both these areas in this work: we use a fast deep neural network to infer semantic and structural information about the environment, and using a Bayesian framework, inject the results into a bundle adjustment process that constrains the 3d point cloud to texture-less 3d building models.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"24 1","pages":"1586-1593"},"PeriodicalIF":0.0,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73020177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-24DOI: 10.1109/IROS.2017.8202228
Gabriele Buondonno, Justin Carpentier, Guilhem Saurel, N. Mansard, Alessandro De Luca, J. Laumond
We present an optimization framework for the design and analysis of underactuated biped walkers, characterized by passive or actuated joints with rigid or non-negligible elastic actuation/transmission elements. The framework is based on optimal control, dealing with geometric constraints and various dynamic objective functions, as well as boundary conditions, which helps in selecting optimal values both for the actuation and the transmission parameters. Solutions of the formulated problems are shown for different kinds of bipedal architectures, and comparisons drawn between traditional rigid robots and compliant ones show the energy-efficiency of compliant actuators in the context of locomotion.
{"title":"Actuator design of compliant walkers via optimal control","authors":"Gabriele Buondonno, Justin Carpentier, Guilhem Saurel, N. Mansard, Alessandro De Luca, J. Laumond","doi":"10.1109/IROS.2017.8202228","DOIUrl":"https://doi.org/10.1109/IROS.2017.8202228","url":null,"abstract":"We present an optimization framework for the design and analysis of underactuated biped walkers, characterized by passive or actuated joints with rigid or non-negligible elastic actuation/transmission elements. The framework is based on optimal control, dealing with geometric constraints and various dynamic objective functions, as well as boundary conditions, which helps in selecting optimal values both for the actuation and the transmission parameters. Solutions of the formulated problems are shown for different kinds of bipedal architectures, and comparisons drawn between traditional rigid robots and compliant ones show the energy-efficiency of compliant actuators in the context of locomotion.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"13 1","pages":"705-711"},"PeriodicalIF":0.0,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76237310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-24DOI: 10.1109/IROS.2017.8206350
A. Bhole, J. Kumle, S. S. Groothuis, R. Carloni
The paper presents a control method to catch a moving object with a joint actuated by means of a variable stiffness actuator. The controller is designed such that the variable stiffness joint acts as a virtual damper that absorbs the kinetic energy of the moving object. The virtual damping and the output stiffness of the variable stiffness actuator are the control variables. To obtain a critically damped system, the damping coefficient is scheduled on both the output stiffness and the inertia of the system. Experiments on the rotational variable stiffness actuator vsaUT-II validate the control method.
{"title":"Control of a variable stiffness joint for catching a moving object","authors":"A. Bhole, J. Kumle, S. S. Groothuis, R. Carloni","doi":"10.1109/IROS.2017.8206350","DOIUrl":"https://doi.org/10.1109/IROS.2017.8206350","url":null,"abstract":"The paper presents a control method to catch a moving object with a joint actuated by means of a variable stiffness actuator. The controller is designed such that the variable stiffness joint acts as a virtual damper that absorbs the kinetic energy of the moving object. The virtual damping and the output stiffness of the variable stiffness actuator are the control variables. To obtain a critically damped system, the damping coefficient is scheduled on both the output stiffness and the inertia of the system. Experiments on the rotational variable stiffness actuator vsaUT-II validate the control method.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"9 1","pages":"4756-4761"},"PeriodicalIF":0.0,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82566185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-24DOI: 10.1109/IROS.2017.8206183
Julien Dupeyroux, J. Diperi, M. Boyron, S. Viollet, J. Serres
In an outdoor autonomous navigational context, classic compass sensors such as magnetometers have to deal with unpredictable magnetic disturbances. In this paper, we propose to get inspiration from the insect navigational abilities to design a celestial compass based on linear polarization of ultraviolet (UV) skylight. To compute the solar meridian relative orientation, our 3D-printed celestial compass uses only two pixels created by two UV-light photo-sensors topped with linear polarizers arranged orthogonally to each other, in the same manner that was observed in insects' Dorsal Rim Area ommatidia. The compass was then embedded on our hexapod walking robot called Hexabot. We first tested the UV-polarized light compass to compensate for yaw random disturbances. We then used the compass to maintain Hexabot's heading direction constant in a straight-forward task, knowing the robot has important yaw drifts. Experiments under various meteorological conditions provided steady state heading direction errors from 0.3° under clear sky conditions to 1.9° under overcast sky, which suggests interesting precision and reliability to make this optical compass suitable for robotics.
{"title":"A novel insect-inspired optical compass sensor for a hexapod walking robot","authors":"Julien Dupeyroux, J. Diperi, M. Boyron, S. Viollet, J. Serres","doi":"10.1109/IROS.2017.8206183","DOIUrl":"https://doi.org/10.1109/IROS.2017.8206183","url":null,"abstract":"In an outdoor autonomous navigational context, classic compass sensors such as magnetometers have to deal with unpredictable magnetic disturbances. In this paper, we propose to get inspiration from the insect navigational abilities to design a celestial compass based on linear polarization of ultraviolet (UV) skylight. To compute the solar meridian relative orientation, our 3D-printed celestial compass uses only two pixels created by two UV-light photo-sensors topped with linear polarizers arranged orthogonally to each other, in the same manner that was observed in insects' Dorsal Rim Area ommatidia. The compass was then embedded on our hexapod walking robot called Hexabot. We first tested the UV-polarized light compass to compensate for yaw random disturbances. We then used the compass to maintain Hexabot's heading direction constant in a straight-forward task, knowing the robot has important yaw drifts. Experiments under various meteorological conditions provided steady state heading direction errors from 0.3° under clear sky conditions to 1.9° under overcast sky, which suggests interesting precision and reliability to make this optical compass suitable for robotics.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"186 1","pages":"3439-3445"},"PeriodicalIF":0.0,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77487021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-24DOI: 10.1109/IROS.2017.8206622
J. Merlet
Direct kinematics (DK) of cable-driven parallel robots (CDPR) based only on cable lengths measurements is a complex issue even with ideal cables and consequently even harder for more realistic cable models such as sagging cable. A natural way to simplify the DK solving is to add sensors. We consider here sensors that give a partial or complete measurement of the cable direction at the anchor points and/or measure the orientation of the platform of CDPR with 2 or 3 cables and we assume that the measurements are exact. We provide a solving procedure and maximal number of DK solutions for an extensive combination of sensors for CDPR with sagging cables. We show that at least two measurements are necessary for the planar 2 cables case while six are necessary for the spatial 3 cables case. For spatial CDPR with n cables we prove that at least 2n additional sensors will be required to get a closed-form solution of the DK.
{"title":"Direct kinematics of CDPR with extra cable orientation sensors: The 2 and 3 cables case with perfect measurement and sagging cables","authors":"J. Merlet","doi":"10.1109/IROS.2017.8206622","DOIUrl":"https://doi.org/10.1109/IROS.2017.8206622","url":null,"abstract":"Direct kinematics (DK) of cable-driven parallel robots (CDPR) based only on cable lengths measurements is a complex issue even with ideal cables and consequently even harder for more realistic cable models such as sagging cable. A natural way to simplify the DK solving is to add sensors. We consider here sensors that give a partial or complete measurement of the cable direction at the anchor points and/or measure the orientation of the platform of CDPR with 2 or 3 cables and we assume that the measurements are exact. We provide a solving procedure and maximal number of DK solutions for an extensive combination of sensors for CDPR with sagging cables. We show that at least two measurements are necessary for the planar 2 cables case while six are necessary for the spatial 3 cables case. For spatial CDPR with n cables we prove that at least 2n additional sensors will be required to get a closed-form solution of the DK.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"147 1","pages":"6973-6978"},"PeriodicalIF":0.0,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73986186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-24DOI: 10.1109/iros.2017.8206420
Ide-Flore Kenmogne, Vincent Drevelle, É. Marchand
This paper proposes an image-based localization method that enables to estimate a bounded domain of the pose of an unmanned aerial vehicle (UAV) from uncertain measurements of known landmarks in the image. The approach computes a domain that should contain the actual robot pose, assuming bounded image measurement errors and landmark position uncertainty. It relies on interval analysis and constraint propagation techniques to rigorously back-propagate the errors through the non-linear observation model. Attitude information from onboard sensors is merged with image observations to reduce the pose uncertainty domain, along with prediction based on velocity measurements. As tracking landmarks in the image is prone to errors, the proposed method also enable fault detection from measurement inconsistencies. This method is tested using a quadcopter UAV with an onboard camera.
{"title":"Image-based UAV localization using interval methods","authors":"Ide-Flore Kenmogne, Vincent Drevelle, É. Marchand","doi":"10.1109/iros.2017.8206420","DOIUrl":"https://doi.org/10.1109/iros.2017.8206420","url":null,"abstract":"This paper proposes an image-based localization method that enables to estimate a bounded domain of the pose of an unmanned aerial vehicle (UAV) from uncertain measurements of known landmarks in the image. The approach computes a domain that should contain the actual robot pose, assuming bounded image measurement errors and landmark position uncertainty. It relies on interval analysis and constraint propagation techniques to rigorously back-propagate the errors through the non-linear observation model. Attitude information from onboard sensors is merged with image observations to reduce the pose uncertainty domain, along with prediction based on velocity measurements. As tracking landmarks in the image is prone to errors, the proposed method also enable fault detection from measurement inconsistencies. This method is tested using a quadcopter UAV with an onboard camera.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"60 2 1","pages":"5285-5291"},"PeriodicalIF":0.0,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77657215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-09-24DOI: 10.1109/IROS.2017.8206111
M. Stefano, J. Artigas, C. Secchi
This paper proposes a passive and explicit integrator for simulating a rotational rigid-body dynamics rendered by a robot. Considering the Euler integration method, active energy terms are identified. These sources of energy are due to the external torque and the coupled dynamics which can lead to a non-physical behavior of the simulated dynamics. The proposed method dissipates this energy using a variable damper regulated by an energy observer. The new algorithm guarantees not only passivity but also a consistent energetic integration. The integration method is sustained by simulations and tested on a real-time hardware-in-the-loop simulator.
{"title":"A passive integration strategy for rendering rotational rigid-body dynamics on a robotic simulator","authors":"M. Stefano, J. Artigas, C. Secchi","doi":"10.1109/IROS.2017.8206111","DOIUrl":"https://doi.org/10.1109/IROS.2017.8206111","url":null,"abstract":"This paper proposes a passive and explicit integrator for simulating a rotational rigid-body dynamics rendered by a robot. Considering the Euler integration method, active energy terms are identified. These sources of energy are due to the external torque and the coupled dynamics which can lead to a non-physical behavior of the simulated dynamics. The proposed method dissipates this energy using a variable damper regulated by an energy observer. The new algorithm guarantees not only passivity but also a consistent energetic integration. The integration method is sustained by simulations and tested on a real-time hardware-in-the-loop simulator.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"43 1","pages":"2806-2812"},"PeriodicalIF":0.0,"publicationDate":"2017-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84549377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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