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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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A robust nonlinear controller for nontrivial quadrotor maneuvers: Approach and verification

A robust nonlinear controller for nontrivial quadrotor maneu...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Yuyi Liu J. M. Montenbruck P. Stegagno F. Allgower A. Zell Department of Computer Science University of Tubingen Tubingen Germany Autonomous Robotics and Human-Machine Systems group Max Planck Institute for Biological Cybernetics Tubingen Germany Institute for Systems Theory and Automatic Control University of Stuttgart Stuttgart Germany Eberhard Karls Universitat Tubingen Tubingen Baden-WÃ¼rttemberg DE

This paper presents a nonlinear control approach for quadrotor Micro Aerial Vehicles (MAVs), which combines a backstepping-like regulator based on the solution of a certain class of global output regulation problems for the rigid body equations on SO(3), a robust controller for the system with bounded disturbances, as well as a trajectory generator using a model predictive control method. The proposed algorithm is endowed with strong convergence properties so that it allows the quadrotor MAVs to reach almost all the desired attitudes. The control approach is implemented on a high-payload-capable quadcopter with unstructured dynamics and unknown disturbances. The performance of our algorithm is demonstrated through a series of experimental evaluations and comparisons with another control method on normal and aggressive trajectory tracking tasks.

关键词： Attitude control Trajectory Robustness Heuristic algorithms Mathematical model Tracking Aerodynamics

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Wheel-Legged Robot – Construction and obstacle detection sensors

Wheel-Legged Robot – Construction and obstacle detection se...

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作者： Gronowicz, A. Sperzyński, P. Szrek, J. Jakubiak, J. Wroclaw University of Technology Division of Machine Theory and Mechatronic Systems Poland Wroclaw University of Technology Institute of Computer Engineering Control and Robotics Poland

ISBN: (纸本)9789400774841

This paper presents the general structure of wheel-legged robot module and sensory systems. The scheme, interfaces and system components will be presented. Basing on initial experiments the sensor properties and suitability for a particular task – detection, identification and overcoming encountered obstacles on the robot’s path were assessed. © Springer Science+Business Media Dordrecht 2014.

关键词： Wheels

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Synchronizing Linear Heterogeneous Networks by Output Homogenization

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IFAC Proceedings Volumes 2014年第3期47卷 4687-4692页

作者： Saman Khodaverdian Jürgen Adamy Institute of Automatic Control and Mechatronics Laboratory of Control Theory and Robotics Technische Universität Darmstadt Germany

This article deals with the synchronization of heterogeneous multi-agent systems. A simple distributed control law is provided to solve the problem. The presented approach is based on the idea to ascribe the heterogeneous case to a homogeneous synchronization task, for which the solution is well known. The presented method is applicable to networks of completely different agents, even with different dimensions. Additionally, the communication effort is minimized because only the states which are to be synchronized need to be exchanged through the network. An example illustrates the efficiency of the concept.

关键词： Synchronization Multi-agent systems Heterogeneous agents Distributed control

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Grid mapping in dynamic road environments: Classification of dynamic cell hypothesis via tracking

Grid mapping in dynamic road environments: Classification of...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Matthias Schreier Volker Willert Jürgen Adamy Institute of Automatic Control and Mechatronics Control Theory and Robotics Lab Darmstadt Germany

We propose a method capable of acquiring an occupancy grid map-based representation of the local, static driving environment around an intelligent vehicle in the presence of dynamic objects. These corrupt the representation due to violating the underlying static-world assumptions of common grid mapping algorithms and are therefore detected and filtered from the map. For this purpose, a subsequent step is suggested that identifies, clusters and merges dynamic cell hypothesis in a novel way. Thereafter, an Interacting-Multiple-Model-Unscented-Kalman-Probabilistic-Data-Association (IMM-UK-PDA) tracker is used to classify of whether cell movements behave consistently with possible movement characteristics of real dynamic objects or are just generated by noise or newly observed static environment. In opposition to many other approaches, the method explicitly combines information of newly occupied and free areas, completes the shape of only partly visible dynamic objects and uses an advanced object tracking scheme to clean the grid from dynamic object corruptions. The method is evaluated with grids generated by an automotive radar and stereo camera in real traffic environments.

关键词： Vehicle dynamics Heuristic algorithms Radar tracking Vehicles Vectors Predictive models Dynamics

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Beyond histograms: Why learned structure-preserving descriptors outperform HOG 22

Beyond histograms: Why learned structure-preserving descript...

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22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014

作者： Guthier, Thomas Willert, Volker Eggert, Julian TU Darmstadt Control Theory and Robotics Lab. Landgraf-Georg-Str. 4 Darmstadt64283 Germany Honda Research Institute Europe Carl-Legien-Str. 30 Offenbach63073 Germany

ISBN: (纸本)9782874190957

Statistical image descriptors based on histograms (e.g. SIFT [1], HOG [2]) are widely used in image processing, because they are fast and simple methods with high classification performance. However, they discard the local spatial topology and thus lose discriminative information contained in the image. We discuss the relations between HOG and VNMF descriptors, i.e. structure free histograms versus learned structure-preserving patterns. VNMF is a shift-invariant, sparse, nonnegative unsupervised learning algorithm [8, 9, 5], that provides a distinct decomposition of the input into its parts. The VNMF descriptor outperforms the statistical HOG descriptor, because it preserves spatial topology leading to better classification results on real-world human action recognition benchmarks [11, 12].

关键词： Graphic methods

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SNN-LDS: Spatio-temporal non-negative sparse coding for human action recognition

SNN-LDS: Spatio-temporal non-negative sparse coding for huma...

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24th International Conference on Artificial Neural Networks, ICANN 2014

作者： Guthier, Thomas Šošić, Adrian Willert, Volker Eggert, Julian Control Theory and Robotics TU Darmstadt Landgraf-Georg Strasse 4 Darmstadt Germany Signal Processing Group TU Darmstadt Merckstrasse 25 Darmstadt Germany Honda Research Institute Europe Carl-Legien Strasse 30 Offenbach Germany

ISBN: (纸本)9783319111780

Current state-of-the-art approaches for visual human action recognition focus on complex local spatio-temporal descriptors, while the spatio-temporal relations between the descriptors are discarded. These bag-of-features (BOF) based methods come with the disadvantage of limited descriptive power, because class-specific mid- and large-scale spatio-temporal information, such as body pose sequences, cannot be represented. To overcome this restriction, we propose sparse non-negative linear dynamical systems (sNN-LDS) as a dynamic, parts-based, spatio-temporal representation of local descriptors. We provide novel learning rules based on sparse non-negative matrix factorization (sNMF) to simultaneously learn both the parts as well as their transitions. On the challenging UCF-Sports dataset our sNN-LDS combined with simple local features is competitive with state-of-the-art BOF-SVM methods. © 2014 Springer International Publishing Switzerland.

关键词： Linear control systems

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Long-term tracking method on ground moving target of UAV

Long-term tracking method on ground moving target of UAV

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2014中国制导、导航与控制学术会议

作者： Qingji Gao Zheng chao Zeng Dandan Hu Computer Science and Technology Robotics InstituteCivil Aviation University of ChinaTianjin 300300China School of navigation guidance and control on aviation institute of automationCivil aviation university of ChinaTianjin300300 China Control Theory and Control EngineeringRobotics InstituteCivil Aviation University of ChinaTianjin 300300China

ISBN: (纸本)9781479946983

The 7th IARC (international aerial robot competition) focus on a long-term and real-time tracking of ground moving target for UAV (unmanned aerial vehicle).This paper proposes a tracking method using Camshift algorithm with color and edge features fusion,which will apply a Phash target detection algorithm basing on perceptual hash *** targets are severely obscured or disappear from view,which will lead tracking failure,whereas targets can be detected and obtained again using the *** results demonstrate that this method can provide a long-term and real-time tracking of ground moving target,which processes both robustness and computational efficiency.

关键词： UAV Target tracking Camshift Perceptual hash algorithm

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Dynamics identification of a damped multi elastic link robot arm under gravity

Dynamics identification of a damped multi elastic link robot...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jörn Malzahn Rene Felix Reinhart Torsten Bertram Institute of Control Theory and Systems Engineering Technische Universität Dortmund Dortmund Germany Research Institute of Cognition & Robotics — CoR-Lab. Bielefeld University Bielefeld Germany

The infinite dimensionality, varying, uncertainties or even unknown boundary conditions render the derivation and - in particular - the identification of accurate dynamics models for elastic link robots tedious and error prone. This contribution circumvents these challenges by the prior application of a model-free inner loop oscillation damping controller before modelling the robot's dynamics. Then, the damped dynamics of a multi elastic link robot arm under gravity can be modelled with high accuracy. An analytical and a data-driven model for the damped dynamics are proposed and quantitatively compared. Both models can explain motor currents as well as link strain measurements in real-time. The paper includes an experimental model validation with different payloads in the entire workspace of the robot.

关键词： Joints Torque Strain Robots Payloads Oscillators Analytical models

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Learning associative spatiotemporal features with non-negative sparse coding

Learning associative spatiotemporal features with non-negati...

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21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2013

作者： Guthier, Thomas Gerges, Steve Willert, Volker Eggert, Julian TU Darmstadt Control theory and robotics lab Landgraf-Georg-Str. 4 64283 Darmstadt Germany Honda Research Institute Europe Carl-Legien-Str. 30 63073 Offenbach Germany

ISBN: (纸本)9782874190810

Motion features based on optical flow are very powerful in tasks such as the recognition of human actions or gestures. Usually, they are combined with gradient information to form a set of spatiotemporal features. However, humans can recognize gestures and actions and thus derive the implied motion out of static images alone. We model this associative recognition within a learned hierarchy of non-negative sparse coding layers. In the first stages, topology preserving gradient and motion features are processed separately. Afterwards, they are projected onto a combined inner representation, that is learned during the training phase. We show, that during recognition the learned, combined representation improves the recognition of human actions, even in the absence of explicit motion information.

关键词： Codes (symbols)

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