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IEEE International Conference on robotics and Automation (ICRA)

作者： Hu Cao Guang Chen Zhijun Li Jianjie Lin Alois Knoll Chair of Robotics Artificial Intelligence and Real-Time Systems Technische Universität München München Germany State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Tongji University Shanghai China University of Science and Technology of China China

This paper proposes an efficient, fully convolutional neural network to generate robotic grasps by using 300×300 depth images as input. Specifically, a residual squeeze-and-excitation network (RSEN) is introduced for deep feature extraction. Following the RSEN block, a multi-scale spatial pyramid module (MSSPM) is developed to obtain multi-scale contextual information. The outputs of each RSEN block and MSSPM are combined as inputs for hierarchical feature fusion. Then, the fused global features are upsampled to perform pixel-wise learning for grasping pose estimation. The experimental results on Cornell and Jacquard grasping datasets indicate that the proposed method has a fast inference speed of 5ms while achieving high grasp detection accuracy of 96.4% and 94.8% on Cornell and Jacquard, respectively, which strikes a balance between accuracy and running speed. Our method also gets a 90% physical grasp success rate with a UR5 robot arm.

关键词： Automation Conferences Pose estimation Grasping Manipulators Feature extraction Inference algorithms

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Efficient TD3 based path planning of mobile robot in dynamic environments using prioritized experience replay and LSTM

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Scientific reports 2025年第1期15卷 18331页

作者： Yunhan Lin Zhijie Zhang Yijian Tan Hao Fu Huasong Min School of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430081 China. Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430081 China. Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan 430081 China. Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan 430081 China. mhuasong@***.

To address the challenges of sample utilization efficiency and managing temporal dependencies, this paper proposes an efficient path planning method for mobile robot in dynamic environments based on an improved twin delayed deep deterministic policy gradient (TD3) algorithm. The proposed method, named PL-TD3, integrates prioritized experience replay (PER) and long short-term memory (LSTM) neural networks, which enhance both sample efficiency and the ability to handle time-series data. To verify the effectiveness of the proposed method, simulation and practical experiments were designed and conducted. In the simulation experiments, both static and dynamic obstacles were included in the test environment, along with experiments to assess generalization capabilities. The algorithm demonstrated superior performance in terms of both execution time and path efficiency. The practical experiments, based on the assumptions from the simulation tests, further confirmed that PL-TD3 has improved the effectiveness and robustness of path planning for mobile robot in dynamic environments.

关键词： Long short-term memory (LSTM ) Path planning in dynamic environment Prioritized experience replay (PER) Reinforcement learning Twin delayed deep deterministic policy gradient (TD3) algorithm

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Development of a Cloud- and Edge-Architecture for adaptive model weight optimization of a CNN exemplified by optical detection of hairpin welding

Development of a Cloud- and Edge-Architecture for adaptive m...

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International Electric Drives Production Conference (EDPC)

作者： Johannes Vater Maximilian Kirschning Dominik Scheurenberg Dirk Abel Alois Knoll Planning and Production of Electrified Powertrains BMW Group Munich Germany Chair of Robotics Artificial Intelligence and Real-time Systems Technical University Munich Munich Germany Institute of Automatic Control RWTH Aachen University Aachen Germany

ISBN: (数字)9781728184586

ISBN: (纸本)9781728196145

The beginning of a global reorientation towards an increasingly conscientious approach to nature and the human habitat has been accompanied by changes in industry and society. The automotive industry, where a transition from combustion to electrically powered vehicles is currently underway, is also concerned with this change. In addition to increasing the capacity of the battery, improving the efficiency of the electric motor is essential. To achieve these goals, however, new technologies such as hairpins for the stator are needed. An important process step involves the welding of two pairs of hairpins, which often leads to welding defects. Nevertheless, expert knowledge in this field is limited. Optical monitoring of the welding process with the help of a convolutional neural network (CNN) is a good approach. This approach can compensate for the low level of expert knowledge and detects and classifies welding defects directly in the production line. However, the disadvantage of optical monitoring is that production conditions and the surrounding environment change over time. This has an impact on optical detection and can negatively affect the accuracy of a CNN. For example, the camera perspective can change, which has a negative effect on optical quality monitoring. Therefore, this paper presents an approach for monitoring and evaluating the quality of a CNN in a cloud instance online. If a deteriorating quality is detected, the CNN in the cloud is re-trained by continuously collected data and then automatically deployed to the production line. This allows the CNN to adapt to the changing environmental conditions. The present approach is demonstrated and validated with real data of the stator production process. Compared with the current state-of-the-art, this control loop is highly automated and requires a minimum of human intervention.

关键词： Industries Welding Production Optical computing Stators Monitoring Optimization

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A General Gray Code Quantized Method of Binary Feature Descriptors for Fast and Efficient Keypoint Matching

A General Gray Code Quantized Method of Binary Feature Descr...

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International Conference on Intelligent Autonomous systems (ICoIAS)

作者： Yunhan Lin Yalan Sun Huasong Min College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial Systems Wuhan China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China

In this paper, a general Gray code quantized method of binary feature descriptors is proposed for fast and efficient keypoint matching on 3D point clouds. In our method, it includes 2 variable L and N. L is rule variable which can be used to set the encoding group length according to the feature of the real-valued descriptor, and N is bits variable which can be used to set the number of Gray code bits according to the actual system requirements. Be different from the exist method, such as B-SHOT, our proposed method has the advantages of reasonable and flexible. As an example, our method is applied on the feature descriptor SHOT and tested in a standard benchmark dataset, different variable combinations of L and N are tested in the Gray code quantized processes, the best combination of L and N is dubbed as GRAY-SHOT through performance comparison. At last, GRAY-SHOT is compared with the state-of-the-art binary 3D feature descriptor B-SHOT, experimental evaluation result shows that GRAY-SHOT offers better keypoint matching performances to B-SHOT on a standard benchmark dataset with a slight more memory footprint and time consumption.

关键词： Three-dimensional displays Reflective binary codes Encoding Histograms Feature extraction Standards Benchmark testing

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Studying bioluminescence flashes with the ANTARES deep Sea neutrino telescope

arXiv

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arXiv 2021年

作者： Reeb, Nico Hutschenreuter, S. Zehetner, P. Ensslin, T. Albert, A. Alves, S. André, M. Anghinolfi, M. Anton, G. Ardid, M. Aubert, J.-J. Aublin, J. Baret, B. Basa, S. Belhorma, B. Bendahman, M. Bertin, V. Biagi, S. Bissinger, M. Boumaaza, J. Bouta, M. Bouwhuis, M.C. Brânzaş, H. Bruijn, R. Brunner, J. Busto, J. Caiffi, B. Capone, A. Caramete, L. Carr, J. Carretero, V. Celli, S. Chabab, M. Chau, T.N. Chiarusi, T. Circella, M. Coleiro, A. Colomer-Molla, M. Coniglione, R. Coyle, P. Creusot, A. Díaz, A.F. de Wasseige, G. Deschamps, A. Distefano, C. Di Palma, I. Domi, A. Donzaud, C. Dornic, D. Drouhin, D. van Eeden, T. Enzenhöfer, A. Fermani, P. Ferrara, G. Filippini, F. Fusco, L. Gatelet, Y. Gay, P. Glotin, H. Gozzini, R. Ruiz, R. Gracia Graf, K. Guidi, C. Hallmann, S. van Haren, H. Heijboer, A.J. Hello, Y. Hernández-Rey, J.J. Hößl, J. Hofestädt, J. Huang, F. Illuminati, G. James, C.W. Jisse-Jung, B. de Jong, M. de Jong, P. Jongen, M. Kadler, M. Kalekin, O. Katz, U. Khan-Chowdhury, N.R. Kouchner, A. Kreykenbohm, I. Kulikovskiy, V. Lahmann, R. Le Breton, R. Lefèvre, D. Leonora, E. Levi, G. Lincetto, M. Lopez-Coto, D. Loucatos, S. Maderer, L. Manczak, J. Marcelin, M. Margiotta, A. Marinelli, A. Martínez-Mora, J.A. Melis, K. Migliozzi, P. Moussa, A. Muller, R. Nauta, L. Navas, S. Nezri, E. Fearraigh, B.Ó. Organokov, M. Pavalaş, G.E. Pellegrino, C. Perrin-Terrin, M. Piattelli, P. Pieterse, C. Poirè, C. Popa, V. Pradier, T. Randazzo, N. Reck, S. Riccobene, G. Romanov, A. Sánchez-Losa, A. Greus, F. Salesa Samtleben, D.F.E. Sanguineti, M. Sapienza, P. Schnabel, J. Schumann, J. Schüssler, F. Spurio, M. Stolarczyk, Th. Taiuti, M. Tingay, S.J. Vallage, B. van Elewyck, V. Versari, F. Viola, S. Vivolo, D. Wilms, J. Zavatarelli, S. Zegarelli, A. Zornoza, J.D. Zúñiga, J. Information Field Theory Group Max Planck Institute for Astrophysics Garching Germany Informatics 6 Chair of Robotics Artificial Intelligence and Real time Systems Technical University of Munich Garching Germany Department of Astrophysics IMAPP Radboud University Nijmegen Nijmegen Netherlands Department of Physics Ludwig-Maximilians University Munich Germany CERN Geneva Switzerland Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Université de Haute Alsace MulhouseF-68200 France IFIC - Instituto de Física Corpuscular CSIC Universitat de València c/ Catedrático José Beltrán 2 Paterna ValenciaE-46980 Spain Technical University of Catalonia Laboratory of Applied Bioacoustics Rambla Exposició Vilanova i la Geltrú Barcelona08800 Spain INFN - Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Centre for Astroparticle Physics Erwin-Rommel-Str. 1 Erlangen91058 Germany Universitat Politècnica de València C/ Paranimf 1 Gandia46730 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France Université de Paris CNRS Astroparticule et Cosmologie ParisF-75013 France Aix Marseille Univ CNRS CNES LAM Marseille France National Center for Energy Sciences and Nuclear Techniques B.P.1382 RabatR. P. 10001 Morocco University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 R.P. Rabat10000 Morocco Via S. Sofia 62 Catania95123 Italy University Mohammed I Laboratory of Physics of Matter and Radiations B.P.717 Oujda6000 Morocco Nikhef Science Park Amsterdam Netherlands Institute of Space Science Bucharest MagureleRO-077125 Romania Universiteit van Amsterdam Instituut voor Hoge-Energie Fysica Science Park 105 Amsterdam1098 XG Netherlands INFN - Sezione di Roma P.le Aldo Moro 2 Roma00185 Italy Dipartimento di Fisica Università La Sapienza P.le Aldo Moro 2 Roma00185 Italy LPHEA Faculty of Science - Semlali Cadi Ayyad University P.O

We develop a novel technique to exploit the extensive data sets provided by underwater neutrino telescopes to gain information on bioluminescence in the deep sea. The passive nature of the telescopes gives us the unique opportunity to infer information on bioluminescent organisms without actively interfering with them. We propose a statistical method that allows us to reconstruct the light emission of individual organisms, as well as their location and movement. A mathematical model is built to describe the measurement process of underwater neutrino telescopes and the signal generation of the biological organisms. The Metric Gaussian Variational Inference algorithm is used to reconstruct the model parameters using photon counts recorded by the neutrino detectors. We apply this method to synthetic data sets and data collected by the ANTARES neutrino telescope. The telescope is located 40 km off the French coast and fixed to the sea floor at a depth of 2475 m. The runs with synthetic data reveal that we can reliably model the emitted bioluminescent flashes of the organisms. Furthermore, we find that the spatial resolution of the localization of light sources highly depends on the configuration of the telescope. Precise measurements of the efficiencies of the detectors and the attenuation length of the water are crucial to reconstruct the light emission. Finally, the application to ANTARES data reveals the first precise localizations of bioluminescent organisms using neutrino telescope data. © 2021, CC BY.

关键词： Bioluminescence

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Adaptive Switching controllers for Tracking with Hybrid Communication Protocols

Adaptive Switching Controllers for Tracking with Hybrid Comm...

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IEEE Annual Conference on Decision and control

作者： Harald Voit Anuradha Annaswamy Reinhard Schneider Dip Goswami Samarjit Chakraborty Institute of Automatic Control Engineering Technische Universitat Munchen Department of Mechanical Engineering Massachussets Institute of Technology Institute for Real-Time Computer Systems Technische Universitat Munchen

ISBN: (纸本)9781467320658

The focus of this paper is on the co-design of control and communication protocol for the control of multiple applications with unknown parameters using a distributed embedded system. The co-design consists of an adaptive switching controller and a hybrid communication architecture that switches between a time-triggered and event-triggered protocol. It is shown that the overall co-design leads to an overall switching adaptive system that has bounded solutions and ensures tracking in the presence of a class of disturbances.

关键词： Co-design controllers Self tuning Communication protocols tracking Adaptive systems Unknown parameter Ensure Switches design control switching switching controller Communication and control HYBRID Hybrid electric vehicles

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Challenges in automotive cyber-physical systems design

Challenges in automotive cyber-physical systems design

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International Conference on Embedded computer systems: Architectures, Modeling and Simulation (IC-SAMOS)

作者： Dip Goswami Reinhard Schneider Alejandro Masrur Martin Lukasiewycz Samarjit Chakraborty Harald Voit Anuradha Annaswamy Institute for Real-Time Computer Systems TU Munich Germany TUM-CREATE Center for Electromobility Singapore Institute for Automatic Control TU Munich Germany Massachusetts Institute of Technology USA

systems with tightly interacting computational (cyber) units and physical systems are generally referred to as cyber-physical systems. They involve an interplay between embedded systems, control theory, real-time systems and software engineering. A very good example of cyber-physical systems design arises in the context of automotive architectures and software. Modern high-end cars have 50-100 processors or electronic control units (ECUs) that communicate over a network of buses such as CAN and FlexRay. In such complex settings, traditional control-theoretic approaches - where control engineers are only concerned with high-level plant and controller models - start breaking down. This is because implementation-level realities such as message delay, jitter, and task execution times are not adequately considered when designing the controller. Hence, it is becoming necessary to adopt a more holistic, cyber-physical systems design approach where the semantic gap between high-level control models and their actual implementations on multiprocessor automotive platforms is quantified and consciously closed. In this paper we give several examples on how this may be done and the current research challenges in this area that are being faced by the academia and the industry.

关键词： Automotive engineering Schedules Algorithm design and analysis Space exploration Delay Mathematical model control systems

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Adaptive Switching controllers for systems with Hybrid Communication Protocols

Adaptive Switching Controllers for Systems with Hybrid Commu...

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American control Conference

作者： Harald Voit Anuradha Annaswamy Reinhard Schneider Dip Goswami Samarjit Chakraborty Institute of Automatic Control Engineering Technische Universitat Munchen D-80290 Munich Germany Department of Mechanical Engineering Massachussets Institute of Technology Cambridge MA 02319 USA Institute for Real-Time Computer Systems Technische Universitat Munchen D-80290 Munich Germany

ISBN: (纸本)9781457710957

Cyber-Physical systems (CPS) are ubiquitous, motivated by the need to integrate control, computing, and communication, increasing capabilities and declining costs of the underlying technologies, and increased requirements on safety, reliability, and performance. The focus of this paper is the co-design of hybrid communication protocol and adaptive switching control that enables stabilization of multiple control applications using minimal communication resources. The hybrid protocol chosen is one that switches between time-triggered and event-triggered methods in order to realize their combined advantages. A control algorithm is co-designed along with this hybrid protocol so as to exploit the properties of the individual protocols as well as the switches between them. The controller is chosen to be adaptive in order to cope with any uncertainties that may be present. The resulting adaptive, switching controller is shown to be stable in the presence of a class of disturbances.

关键词： Self tuning controllers Communication protocols Switches communication resources HYBRID Hybrid electric vehicles Co-design computer algorithms protocols switching switching controller

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Team AnnieWAY's autonomous system for the DARPA Urban Challenge 2007

Team AnnieWAY's autonomous system for the DARPA Urban Challe...

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作者： Kammel, Sören Ziegler, Julius Pitzer, Benjamin Werling, Moritz Gindele, Tobias Jagzent, Daniel Schöder, Joachim Thuy, Michael Goebl, Matthias Von Hundelshausen, Felix Pink, Oliver Frese, Christian Stiller, Christoph Institute for Measurement and Control University of Karlsruhe Karlsruhe 76131 Germany Institute for Applied Computer Science/Automation University of Karlsruhe Karlsruhe 76128 Germany Industrial Applications of Informatics and Microsystems University of Karlsruhe Karlsruhe 76131 Germany Institute for Distributed Measurement Systems Technical University of Munich Munich 80290 Germany Institute for Institute for Real-Time Computer Systems Technical University of Munich Munich 80290 Germany Department of Aerospace Engineering University of the Federal Armed Forces Neubiberg 85577 Germany

ISBN: (纸本)9783642039904

This paper reports on AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that has successfully entered the finals of the 2007 DARPA Urban Challenge competition. After describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algorithms. Environmental perception mainly relies on a recent laser scanner which delivers both range and reflectivity measurements. While range measurements are used to provide 3D scene geometry, measuring reflectivity allows for robust lane marker detection. Mission and maneuver planning is conducted using a concurrent hierarchical state machine that generates behavior in accordance with California traffic laws. We conclude with a report of the results achieved during the competition. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Reflection

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Motivation and Competitive Learning in a Social Robot

Motivation and Competitive Learning in a Social Robot

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Dominguez, Salvador Zalama, Eduardo Garcia-Bermejo, Jaime G. Pulido, Jaime CARTIF Foundation Robotics Computer Vision and Real Time Division Boecillo Valladolid Spain University of Valladolid (Spain) Dep. of Systems Engineering and Automatic Control Industrial Engineering School Spain

ISBN: (纸本)9781424420575

This paper describes the motivation and learning subsystems of Arisco which is a mechatronic head with interactive capacity which includes high expressivity through gesturing, voice recognition, text to speech generation, visual tracking, and internet information retrieval. The general architecture is first described in the paper. Then, the learning capacity of Arisen is addressed. It learns and performs associations between different stimulus responses through several dynamic neural networks, guided by motivational drives. A number of experiments are discussed, covering stimulus competition, habituation, classical and operant conditioning.

关键词： Social robot learning interaction computer vision motivation

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