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arXiv 2017年

作者： Pajarinen, Joni Kyrki, Ville Koval, Michael Srinivasa, Siddhartha Peters, Jan Neumann, Gerhard labs TU Darmstadt Germany Department of Electrical Engineering and Automation Aalto University Finland Robotics Institute Carnegie Mellon University United States IAS lab TU Darmstadt Germany Max Planck Institute for Intelligent Systems Tuebingen Germany Lincoln Centre for Autonomous Systems University of Lincoln United Kingdom

— Trajectory optimization is a fundamental problem in robotics. While optimization of continuous control trajectories is well developed, many applications require both discrete and continuous, i.e. hybrid controls. Finding an optimal sequence of hybrid controls is challenging due to the exponential explosion of discrete control combinations. Our method, based on Differential Dynamic Programming (DDP), circumvents this problem by incorporating discrete actions inside DDP: we first optimize continuous mixtures of discrete actions, and, subsequently force the mixtures into fully discrete actions. Moreover, we show how our approach can be extended to partially observable Markov decision processes (POMDPs) for trajectory planning under uncertainty. We validate the approach in a car driving problem where the robot has to switch discrete gears and in a box pushing application where the robot can switch the side of the box to push. The pose and the friction parameters of the pushed box are initially unknown and only indirectly observable. Copyright © 2017, The Authors. All rights reserved.

关键词： Aerodynamics

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Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification 17th

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17th International Conference on Asia Simulation, AsiaSim 2017

作者： Prathama, Yohanes de Britto Hertyasta Shapiai, Mohd Ibrahim Aris, Siti Armiza Mohd Ibrahim, Zuwairie Jaafar, Jafreezal Fauzi, Hilman Department of Electronic Systems Engineering Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala LumpurWP Kuala Lumpur54100 Malaysia Centre for Artificial Intelligence and Robotics Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala LumpurWP Kuala Lumpur54100 Malaysia Razak School of Engineering and Advanced Technology Universiti Teknologi Malaysia Jalan Sultan Yahya Petra Kuala LumpurWP Kuala Lumpur54100 Malaysia Faculty of Electrical and Electronic Engineering Universiti Malaysia Pahang PekanPahang26600 Malaysia Department of Computer and Information Sciences Faculty of Science and Information Technology Universiti Teknologi Petronas Seri Iskandar Malaysia Faculty of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (纸本)9789811064623

Brain-Computer Interface (BCI) is a way to translate human thoughts into computer commands. One of the most popular BCI type is Electroencephalography (EEG)-based BCI, where motor imagery is considered one of the most effective ways. Previously, to extract useful information, various filters are introduced, such as spatial, temporal, and spectral filtering. A spatial filtering algorithm called Common Spatial Pattern (CSP) was developed and known to have excellent performance, especially in motor imagery for BCI application. In general, there are several approaches in improving CSP such as regularization approach, analytic approach, and frequency band selection. In general, the existing techniques for band selection is either to select or reject the band by ignoring the importance of the band. For example, Binary Particle Search Optimization Common Spatial Pattern (BPSO-CSP) was proposed to choose multiple possible best bands to be used in processing the data. In this paper, we propose an algorithm called Feature Scaling Common Spatial Pattern (FSc-CSP) to overcome the problem of feature selection. Instead of selecting features, the proposed algorithm employs a feature scaling system to scale the importance of each band by using Genetic Algorithm (GA) altogether with Extreme Learning Machine (ELM) as classifier, with 1 signifying the most important bands, declining until 0 for the unused bands, as opposed to the 1 and 0 selection system used in BPSO-CSP. Conducted experiments show that by employing feature scaling, better results can be achieved especially compared to vanilla CSP and feature selection with 100 hidden nodes in three from five BCI Competition III datasets IVa, namely aa, aw and ay, with around 5–8% better results compared to vanilla CSP and feature selection. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Brain computer interface

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LiDAR-Based control of autonomous rotorcraft for the inspection of pier-like structures: Proofs

arXiv

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arXiv 2017年

作者： Guerreiro, Bruno J. Silvestre, Carlos Cunha, Rita Cabecinhas, David Institute for Systems and Robotics LARSyS Instituto Superior Técnico Universidade de Lisboa Av. Rovisco Pais 1 Lisboa1049 Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Taipa Macau IST

This is a complementary document to the paper presented in [1], where more detailed proofs are provided for some results. The main paper addresses the problem of trajectory tracking control of autonomous rotorcraft in operation scenarios where only relative position measurements obtained from LiDAR sensors are possible. The proposed approach defines an alternative kinematic model, directly based on LiDAR measurements, and uses a trajectory-dependent error space to express the dynamic model of the vehicle. An LPV representation with piecewise affine dependence on the parameters is adopted to describe the error dynamics over a set of predefined operating regions, and a continuous-time H2 control problem is solved using LMIs and implemented within the scope of gain-scheduling control theory. In this document, Section A presents the stability analysis of the attitude inner-loop presented in [1, Section II.B], whereas Section B presents a more detailed version of the stability and performance guarantees for the LPV system, extending the results presented in [1, Section IV.A]. Copyright © 2017, The Authors. All rights reserved.

关键词： Continuous time systems

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A study on the impact of locality in the decoding of binary cyclic codes

arXiv

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arXiv 2017年

作者： Nikhil Krishnan, M. Puranik, Bhagyashree Vijay Kumar, P. Tamo, Itzhak Barg, Alexander Department of Electrical Communication Engineering Indian Institute of Science Bangalore India University of Southern California United States Department of EE-Systems Tel Aviv University Tel Aviv Israel Dept. of ECE and ISR University of Maryland College Park United States Russian Academy of Sciences Moscow Russia

In this paper, we study the impact of locality on the decoding of binary cyclic codes under two approaches, namely ordered statistics decoding (OSD) and trellis decoding. Given a binary cyclic code having locality or availability, we suitably modify the OSD to obtain gains in terms of the Signal-To-Noise ratio, for a given reliability and essentially the same level of decoder complexity. With regard to trellis decoding, we show that careful introduction of locality results in the creation of cyclic subcodes having lower maximum state complexity. We also present a simple upper-bounding technique on the state complexity profile, based on the zeros of the code. Finally, it is shown how the decoding speed can be significantly increased in the presence of locality, in the moderate-to-high SNR regime, by making use of a quick-look decoder that often returns the ML codeword. Copyright © 2017, The Authors. All rights reserved.

关键词： Decoding

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Computationally efficient learning in large-scale games: Sampled fictitious play revisited

Computationally efficient learning in large-scale games: Sam...

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Asilomar Conference on Signals, systems & Computers

作者： Brian Swenson Soummya Kar João Xavier Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA Institute for Systems and Robotics (ISR/IST) Universidade de Lisboa Portugal

ISBN: (纸本)9781538639559

Fictitious Play (FP) is a popular algorithm known to achieve Nash equilibrium learning in certain large-scale games. However, for games with many players, the computational demands of the FP algorithm can be prohibitive. Sampled FP (SFP) is a variant of FP that mitigates computational demands via a Monte Carlo approach. While SFP does mitigate the complexity of FP, it can be shown that SFP still uses information in an inefficient manner. The paper generalizes the SFP convergence result and studies a stochastic-approximation-based variant that significantly reduces the complexity of SFP.

关键词： Games Convergence Monte Carlo methods Approximation algorithms Complexity theory Probability distribution Nash equilibrium

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Integrated mechatronics design of flexure joint and controller in dual-drive gantry: a constrained H2 optimization approach

Integrated mechatronics design of flexure joint and controll...

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2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017

作者： Ma, Jun Chen, Si-Lu Kamaldin, Nazir Teo, Chek Sing Tay, Arthur Mamun, Abdullah Al Tan, Kok Kiong Department of Electrical and Computer Engineering SIMTech-NUS Joint Lab on Precision Motion Systems National University of Singapore 117582 Singapore Department of Electrical and Computer Engineering National University of Singapore 117576 Singapore Mechatronics Group Singapore Institute of Manufacturing Technology 138634 Singapore Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo Zhejiang315121 China NUS Grad. School for Inte. Sci. and Eng. and Department of Electrical Computer Engineering National University of Singapore 119077 Singapore

ISBN: (纸本)9781509059980

The dual-drive H gantry is widely used in many industrial processes that require high precision Cartesian motion. The conventional rigid-link version suffers breaking down of joints if any de-synchronization between the two carriages occurs. To prevent above potential risk, a novel biaxial gantry with flexure-links is designed to allow a small rotation angle of the cross-Arm. Nevertheless, the chattering of control signals and inappropriate design of the flexure joint will possibly induce resonant modes of the end effector. Thus, in this work, the design requirements in terms of tracking accuracy, biaxial synchronization, and resonant mode suppression are achieved by integrated optimization of the stiffness of flexures and PID controller parameters for a class of point-To-point trajectories with same dynamics but different steps. From here, an H2 optimization with defined constraints is formulated, and an efficient iterative solver is proposed by hybridizing direct computation of constrained projection gradient and line search of optimal steps. Comparative experiments results obtained on the testbed are presented to verify the effectiveness of proposed method. © 2017 IEEE.

关键词： Constrained optimization

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Influence of slot geometry on air gap magnetic flux density of rotating machines

Influence of slot geometry on air gap magnetic flux density ...

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IEEE International Conference on Environment and electrical engineering

作者： Rodrigo Alves de Lima A. C. Paulo Coimbra Tony Almeida Viviane Margarida Gomes Thiago Martins Pereira Aylton José Alves Wesley Pacheco Calixto Program in Electronic Systems and Automation PGEA Department of Electrical Engineering ENE University of Brasilia UnB Institute of Systems and Robotics ISR University of Coimbra UC Experimental & Technological Research and Study Group NExT Federal Institute of Goias IFG

ISBN: (纸本)9781509023219

The objective of this work is to investigate the influence of slotted air gap constructive parameters on magnetic flux density of rotating machines. For this purpose, different approaches were used to solve the air gap field diagram using finite element method and the magnetic field distribution uniformity was evaluated by Carter's factor calculation. Sensitivity analysis of slot constructive parameters was performed and results show that slot geometry modifies the magnetic flux on air gap and shifts the air gap magnetic equipotential midline of double slotted machines.

关键词： Carter's factor finite elements method rotating machines

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Hybrid single node genetic programming for symbolic regression 7

Hybrid single node genetic programming for symbolic regressi...

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7th International Joint Conference on Computational Intelligence, IJCCI 2015

作者： Kubalìk, Jiřì Alibekov, Eduard Žegklitz, Jan Babuška, Robert Czech Institute of Informatics Robotics and Cybernetics CTU in Prague Prague Czech Republic Department of Cybernetics Faculty of Electrical Engineering CTU in Prague Prague Czech Republic Delft Center for Systems and Control Delft University of Technology Delft Netherlands

ISBN: (纸本)9783662535240

This paper presents a first step of our research on designing an effective and efficient GP-based method for symbolic regression. First, we propose three extensions of the standard Single Node GP, namely (1) a selection strategy for choosing nodes to be mutated based on depth and performance of the nodes, (2) operators for placing a compact version of the best-performing graph to the beginning and to the end of the population, respectively, and (3) a local search strategy with multiple mutations applied in each iteration. All the proposed modifications have been experimentally evaluated on five symbolic regression benchmarks and compared with standard GP and SNGP. The achieved results are promising showing the potential of the proposed modifications to improve the performance of the SNGP algorithm. We then propose two variants of hybrid SNGP utilizing a linear regression technique, LASSO, to improve its performance. The proposed algorithms have been compared to the state-of-the-art symbolic regression methods that also make use of the linear regression techniques on four real-world benchmarks. The results show the hybrid SNGP algorithms are at least competitive with or better than the compared methods. © Springer-Verlag Berlin Heidelberg 2016.

关键词： Genetic programming

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DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self

arXiv

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arXiv 2017年

作者： Moulin-Frier, Clément Fischer, Tobias Petit, Maxime Pointeau, Grégoire Puigbo, Jordi-Ysard Pattacini, Ugo Low, Sock Ching Camilleri, Daniel Nguyen, Phuong Hoffmann, Matej Chang, Hyung Jin Zambelli, Martina Mealier, Anne-Laure Damianou, Andreas Metta, Giorgio Prescott, Tony J. Demiris, Yiannis Dominey, Peter Ford Verschure, Paul F.M.J. Laboratory for Synthetic Perceptive Emotive and Cognitive Systems Universitat Pompeu Fabra Barcelona08002 Spain Barcelona Spain Personal Robotics Laboratory Department of Electrical and Electronic Engineering Imperial College London SW7 2AZ United Kingdom Robot Cognition Laboratory INSERM U846 Stem Cell and Brain Research Institute Bron69675 France Italian Institute of Technology iCub Facility Via Morego 30 Genova Italy Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Department of Computer Science University of Sheffield United Kingdom

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users. Copyright © 2017, The Authors. All rights reserved.

关键词： Human robot interaction

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Stator Winding Short-Circuit Fault Diagnosis in Induction Motors using Random Forest

Stator Winding Short-Circuit Fault Diagnosis in Induction Mo...

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IEEE International Electric Machines and Drives Conference

作者： Tiago dos Santos Fernando J. T. E. Ferreira Joao Moura Pires Carlos Damasio Department of Computer Science NOVA-LINCS Nova University of Lisbon (FCT/UNL) Lisbon Portugal Dep. of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal

ISBN: (纸本)9781509042821

In this paper, an approach to detect stator winding short-circuit faults in squirrel-cage induction motors based on Random Forest and Park's Vector is proposed. This is accomplished by scoring the unbalance in the current and voltage waveforms as well as in Park's Vector, both for current and voltage. To score the unbalance in the d-q space, a Principal Component Analysis is applied to Park's Vector and with the first two principal components the eccentricity is calculated, while the first principal component is used to determine the phase in short-circuit. The proposed strategy has been experimentally tested on a special 400-V, 50-Hz, 4-pole, 2.2-kW induction motor with reconfigurable stator windings in which it was possible to emulate different types of inter-turn short-circuits. The results are quite promising, even only using 1-kHz sampling frequency to acquire the current and voltage waveforms in the three phases, and the use of the Fast Fourier Transform is avoided. The developed solution may be used for tele-monitoring of the motor condition and to implement advanced predictive maintenance strategies.

关键词： Fault diagnosis Induction motor Inter-turn short-circuit Stator winding PCA Predictive maintenance Machine learning Classification Random forest

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