Pub Date : 2022-01-01DOI: 10.5220/0011279000003271
Arne Hasselbring, U. Frese, T. Röfer
{"title":"Learning Optimal Robot Ball Catching Trajectories Directly from the Model-based Trajectory Loss","authors":"Arne Hasselbring, U. Frese, T. Röfer","doi":"10.5220/0011279000003271","DOIUrl":"https://doi.org/10.5220/0011279000003271","url":null,"abstract":"","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"31 1","pages":"201-208"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89423616","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 : 2022-01-01DOI: 10.5220/0011347500003271
Nikita Shopa, D. Konovalov, A. Kremlev, K. Zimenko
: Sufficient conditions of finite-time stability are presented for the class of nonlinear descriptor systems. Both, explicit and implicit Lyapunov function methods, are extended for finite-time stability analysis of descriptor systems and the corresponding settling time estimates are obtained. The theoretical results are supported by numerical examples.
{"title":"Finite-time Stability Analysis for Nonlinear Descriptor Systems","authors":"Nikita Shopa, D. Konovalov, A. Kremlev, K. Zimenko","doi":"10.5220/0011347500003271","DOIUrl":"https://doi.org/10.5220/0011347500003271","url":null,"abstract":": Sufficient conditions of finite-time stability are presented for the class of nonlinear descriptor systems. Both, explicit and implicit Lyapunov function methods, are extended for finite-time stability analysis of descriptor systems and the corresponding settling time estimates are obtained. The theoretical results are supported by numerical examples.","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"113 1","pages":"711-716"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79399147","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 : 2022-01-01DOI: 10.5220/0011142900003271
Tonja Heinemann, Marwin Gihr, O. Riedel, A. Lechler
: This work analyzes the Open Platform Communications Unified Architecture (OPC UA) specifications for flat glass, plastics and rubber, machine vision, ISA-95 and machine tools regarding their job descriptions. Common contents of job models in the domain of machinery are deducted. Using a structured qualitative content analysis, more than 70 functional elements used in OPC UA job models have been identified. While some of these functional elements are modeled similarly in multiple domains, major differences are identified for other functional elements. Especially those differences constitute impediments in the standardization of industrial communication. The results of this work harmonize the contents and the modeling techniques regarding machining jobs in OPC UA and provide a generally applicable method for the standardization of machine communication throughout different domains. With this method for standardization, this work contributes directly to the goal of OPC UA, to easily exchange data between platforms from multiple vendors.
{"title":"Towards Data-driven Production: Analysis of Data Models Describing Machinery Jobs in OPC UA","authors":"Tonja Heinemann, Marwin Gihr, O. Riedel, A. Lechler","doi":"10.5220/0011142900003271","DOIUrl":"https://doi.org/10.5220/0011142900003271","url":null,"abstract":": This work analyzes the Open Platform Communications Unified Architecture (OPC UA) specifications for flat glass, plastics and rubber, machine vision, ISA-95 and machine tools regarding their job descriptions. Common contents of job models in the domain of machinery are deducted. Using a structured qualitative content analysis, more than 70 functional elements used in OPC UA job models have been identified. While some of these functional elements are modeled similarly in multiple domains, major differences are identified for other functional elements. Especially those differences constitute impediments in the standardization of industrial communication. The results of this work harmonize the contents and the modeling techniques regarding machining jobs in OPC UA and provide a generally applicable method for the standardization of machine communication throughout different domains. With this method for standardization, this work contributes directly to the goal of OPC UA, to easily exchange data between platforms from multiple vendors.","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"1 1","pages":"729-736"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90429668","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 : 2022-01-01DOI: 10.5220/0011317100003271
Elhaouari Kobzili, Ahmed Allam, C. Larbes
: This paper presents a comparative study of scale recovering in monocular simultaneous localization and mapping (Mono-SLAM) by adopting and adapting four estimators into a multi-rate fusion mechanism and considering the scale as an element of the state vector. These estimators are: extended Kalman filter (EKF), smooth variable structure filter (SVSF), combined SVSF-EKF, and particularly adaptive smooth variable structure filter (ASVSF). The use of the ASVSF estimator represents the novelty of this paper because it provides a robust estimation of the trajectory scale as well as the covariance matrix at each iteration. This later represents the estimation incertitude. A second sensor is involved (inertial measurement unit (IMU)) as a reference to align the up to scale trajectory provided by the Mono-SLAM box. The designed system allows finding the scale factor with a rate not further than the IMU frequency and avoids complex synchronization. In order to outline the limitation of each estimator used for scale recovering, a deep analysis of the proposed approaches in terms of robustness, stability, accuracy, and real-time constraint was carried out.
{"title":"Comparative Study between EKF, SVSF, Combined SVSF-EKF, and ASVSF Approaches based Scale Estimation of Monocular SLAM","authors":"Elhaouari Kobzili, Ahmed Allam, C. Larbes","doi":"10.5220/0011317100003271","DOIUrl":"https://doi.org/10.5220/0011317100003271","url":null,"abstract":": This paper presents a comparative study of scale recovering in monocular simultaneous localization and mapping (Mono-SLAM) by adopting and adapting four estimators into a multi-rate fusion mechanism and considering the scale as an element of the state vector. These estimators are: extended Kalman filter (EKF), smooth variable structure filter (SVSF), combined SVSF-EKF, and particularly adaptive smooth variable structure filter (ASVSF). The use of the ASVSF estimator represents the novelty of this paper because it provides a robust estimation of the trajectory scale as well as the covariance matrix at each iteration. This later represents the estimation incertitude. A second sensor is involved (inertial measurement unit (IMU)) as a reference to align the up to scale trajectory provided by the Mono-SLAM box. The designed system allows finding the scale factor with a rate not further than the IMU frequency and avoids complex synchronization. In order to outline the limitation of each estimator used for scale recovering, a deep analysis of the proposed approaches in terms of robustness, stability, accuracy, and real-time constraint was carried out.","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"18 1","pages":"668-679"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88614553","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 : 2022-01-01DOI: 10.5220/0011296200003271
K. Nielsen, Tom N. Pedersen
{"title":"A Planning Tool for COD Flow Optimisation to a Waste Water Treatment Plant","authors":"K. Nielsen, Tom N. Pedersen","doi":"10.5220/0011296200003271","DOIUrl":"https://doi.org/10.5220/0011296200003271","url":null,"abstract":"","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"10 1","pages":"222-229"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75306393","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 : 2022-01-01DOI: 10.5220/0011142200003271
S. Ibarra, V. Vigneron, J.-Ph. Conge, H. Maaref
: Much of convolutional neural network (CNN)’s success lies in translation invariance. The other part resides in the fact that thanks to a judicious choice of architecture, the network is able to make decisions taking into account the whole image. This work provides an alternative way to extend the pooling function, we named rank-order pooling, capable of extracting texture descriptors from images. The rank-order pooling layers are non parametric, independent of the geometric arrangement or sizes of the image regions, and can therefore better tolerate rotations. Rank-order pooling functions produce images capable of emphasizing low/high frequencies, contours, etc. We shows rank-order pooling leads to CNN models which can optimally exploit information from their receptive field.
{"title":"Importance Order Ranking for Texture Extraction: A More Efficient Pooling Operator Than Max Pooling?","authors":"S. Ibarra, V. Vigneron, J.-Ph. Conge, H. Maaref","doi":"10.5220/0011142200003271","DOIUrl":"https://doi.org/10.5220/0011142200003271","url":null,"abstract":": Much of convolutional neural network (CNN)’s success lies in translation invariance. The other part resides in the fact that thanks to a judicious choice of architecture, the network is able to make decisions taking into account the whole image. This work provides an alternative way to extend the pooling function, we named rank-order pooling, capable of extracting texture descriptors from images. The rank-order pooling layers are non parametric, independent of the geometric arrangement or sizes of the image regions, and can therefore better tolerate rotations. Rank-order pooling functions produce images capable of emphasizing low/high frequencies, contours, etc. We shows rank-order pooling leads to CNN models which can optimally exploit information from their receptive field.","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"13 1","pages":"585-594"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91135055","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 : 2022-01-01DOI: 10.5220/0011140800003271
Stephan Pareigis, F. Maaß
: A neural network architecture for end-to-end autonomous driving is presented, which is robust against discrep-ancies in system dynamics during the training process and in application. The proposed network architecture presents a first step to alleviate the simulation to reality gap with respect to differences in system dynamics. A vehicle is trained to drive inside a given lane in the CARLA simulator. The data is used to train NVIDIA’s PilotNet. When an offset is given to the steering angle of the vehicle while the trained network is being applied, PilotNet will not keep the vehicle inside the lane as expected. A new architecture is proposed called PilotNet ∆ , which is robust against steering angle offsets. Experiments in the simulator show that the vehicle will stay in the lane, although the steering properties of the vehicle differ.
{"title":"Robust Neural Network for Sim-to-Real Gap in End-to-End Autonomous Driving","authors":"Stephan Pareigis, F. Maaß","doi":"10.5220/0011140800003271","DOIUrl":"https://doi.org/10.5220/0011140800003271","url":null,"abstract":": A neural network architecture for end-to-end autonomous driving is presented, which is robust against discrep-ancies in system dynamics during the training process and in application. The proposed network architecture presents a first step to alleviate the simulation to reality gap with respect to differences in system dynamics. A vehicle is trained to drive inside a given lane in the CARLA simulator. The data is used to train NVIDIA’s PilotNet. When an offset is given to the steering angle of the vehicle while the trained network is being applied, PilotNet will not keep the vehicle inside the lane as expected. A new architecture is proposed called PilotNet ∆ , which is robust against steering angle offsets. Experiments in the simulator show that the vehicle will stay in the lane, although the steering properties of the vehicle differ.","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"1 1","pages":"113-119"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82235961","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 : 2022-01-01DOI: 10.5220/0011355200003271
Ruslan Gabdrahmanov, T. Tsoy, Yang Bai, M. Svinin, E. Magid
{"title":"Gear Wheels based Simulation of Crawlers for Mobile Robot Servosila Engineer","authors":"Ruslan Gabdrahmanov, T. Tsoy, Yang Bai, M. Svinin, E. Magid","doi":"10.5220/0011355200003271","DOIUrl":"https://doi.org/10.5220/0011355200003271","url":null,"abstract":"","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"78 51 1","pages":"565-572"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90757493","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 : 2022-01-01DOI: 10.5220/0011314000003271
Kai Zhang, E. Lucet, Julien Alexandre Dit Sandretto, Selma Kchir, David Filliat
{"title":"Task and Motion Planning Methods: Applications and Limitations","authors":"Kai Zhang, E. Lucet, Julien Alexandre Dit Sandretto, Selma Kchir, David Filliat","doi":"10.5220/0011314000003271","DOIUrl":"https://doi.org/10.5220/0011314000003271","url":null,"abstract":"","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"29 1","pages":"476-483"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86816818","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 : 2022-01-01DOI: 10.5220/0011336700003271
N. Kolesnik, A. Margun, A. Kremlev, Andrei Zhivitskii
: The paper is devoted to the development of an adaptive approach to the fault detection and isolation of input and sensor failures of armature-controlled direct current motors. The proposed detection method is based on the full state Luenberger observer. Isolation scheme uses the directional residual set and relationships between fault directions and residual vector. Adaptability is provided by dynamic regressor extension and mixing approach for online estimation of parameters. Proposed scheme allows to isolate following faults: unaccounted load acting on the rotor, input voltage disturbance, failures of velocity and current sensors. Simulation results confirm performance of the proposed approach.
{"title":"Adaptive Fault Detection and Isolation for DC Motor Input and Sensors","authors":"N. Kolesnik, A. Margun, A. Kremlev, Andrei Zhivitskii","doi":"10.5220/0011336700003271","DOIUrl":"https://doi.org/10.5220/0011336700003271","url":null,"abstract":": The paper is devoted to the development of an adaptive approach to the fault detection and isolation of input and sensor failures of armature-controlled direct current motors. The proposed detection method is based on the full state Luenberger observer. Isolation scheme uses the directional residual set and relationships between fault directions and residual vector. Adaptability is provided by dynamic regressor extension and mixing approach for online estimation of parameters. Proposed scheme allows to isolate following faults: unaccounted load acting on the rotor, input voltage disturbance, failures of velocity and current sensors. Simulation results confirm performance of the proposed approach.","PeriodicalId":6436,"journal":{"name":"2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010)","volume":"123 1","pages":"703-710"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86283668","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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