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Relaxed conditions for uniform complete observability and controllability of LTV systems with bounded realizations

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IFAC-PapersOnLine 2017年第1期50卷 3598-3605页

作者： Batista P. Petit N. Silvestre C. Oliveira P. Institute for Systems and Robotics Laboratory for Robotics and Engineering Systems Instituto Superior Técnico Universidade de Lisboa Portugal MINES ParisTech PSL Research University CAS – Centre automatique et systémes 60 bd St Michel Paris 75272 France Department of Electrical and Computer Engineering Faculty of Science and Technology of the University of Macau Macau Department of Mechanical Engineering Instituto Superior Técnico Universidade de Lisboa Portugal

Uniform complete observability and controllability are key concepts for the design of state observers and controllers for linear time-varying systems. While the definitions of these properties are simple, it is more often that not very difficult to show they hold for a particular system. This paper presents alternative simpler sufficient conditions. Examples are shown that illustrate the improvement over previous results, the fact that the new conditions are not necessary, and a practical application. © 2017

关键词： linear time-varying systems uniform complete controllability uniform complete observability

Real-time force control of an SEA-based body weight support unit with the 2-DOF control structure

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arXiv 2018年

作者： Sun, Yubo Lei, Yuqi Zou, Wulin Li, Jianmin Yu, Ningbo Institute of Robotics and Automatic Information Systems Nankai University Haihe Education Park Tianjin300353 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Haihe Education Park Tianjin300353 China Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States School of Mechanical Engineering Tianjin University Tianjin300072 China

Body weight support (BWS) is a fundamental technique in rehabilitation. Along with the dramatic progressing of rehabilitation science and engineering, BWS is quickly evolving with new initiatives and has attracted deep research effort in recent years. We have built up a novel gravity offloading system, in which the patient is allowed to move freely in the three-dimensional Cartesian space and receives support against gravity. Thus, the patients, especially for those that suffer from neurological injury such as stroke or spinal cord injury, can focus their residual motor control capabilities on essential therapeutic trainings of balance and gait. The realtime force control performance is critical for the BWS unit to provide suitable support and avoid disturbance. In this work, we have re-designed our BWS unit with a series elastic actuation structure to improve the human-robot interaction performance. Further, the 2 degrees of freedom (2-DOF) control approach was taken for accurate and robust BWS force control. Both simulation and experimental results have validated the efficacy of the BWS design and real-time control methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Force control

Compositional transient stability analysis of power systems via the computation of reachable sets

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Compositional transient stability analysis of power systems ...

American Control Conference

作者： Ahmed El-Guindy Yu Christine Chen Matthias Althoff Institute of Robotics and Embedded Systems Technische Universitat Munchen Department of Electrical and Computer Engineering at the University of British Columbia

ISBN: (纸本)9781509045839

The main challenge associated with the analysis of power systems via the computation of reachable sets is improving the algorithmic efficiency to scale towards industrially relevant problem sizes. In this paper, we present a compositional algorithm that can drastically reduce the computational effort required to assess the dynamical response of power systems during transients using reachability analysis. The main reason for the algorithmic efficiency is that we reformulate the transmission network into a set of subsystems, each consisting of a synchronous generator connected to a generator bus, whose algebraic constraints are unknown-but-bounded within some confidence intervals. This makes it possible to parallelize the computation of reachable sets for transient stability analysis and, more importantly, preserve the interaction and correlation between different machines connected to the grid. The applicability of the proposed compositional algorithm is illustrated on several benchmark examples and compared to other algorithms that compute the reachable set without employing any compositional techniques.

关键词： Transient stability analysis Dynamic security assessment Power systems Reachability analysis power systems transient stability reachability analysis dynamic security assessment transmission networks Stability analysis

Discrete-time distributed Kalman filter design for multi-vehicle systems

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Discrete-time distributed Kalman filter design for multi-veh...

American Control Conference

作者： Daniel Viegas Pedro Batista Paulo Oliveira Carlos Silvestre Department of Electrical and Computer Engineering of the Faculty of Science and Technology of the University of Macau China Institute for Systems and Robotics (ISR) Instituto Superior Tecnico Universidade de Lisboa Portugal ISR and IDMEC Instituto Superior Tecnico Universidade de Lisboa Portugal

ISBN: (纸本)9781509045839

This paper addresses the problem of distributed state estimation in a multi-vehicle framework. In the scenario envisioned in this work, each vehicle aims to estimate its own state by implementing a local state observer which relies on locally available measurements and limited communication with other vehicles in the vicinity. The dynamics of the problem are formulated as a more general discrete-time Kalman filtering problem with a sparsity constraint on the gain and, based on this formulation, a method for computation of steady-state observer gains for arbitrary fixed measurement topologies is introduced. The proposed method consists in the optimization of the time-varying distributed Kalman filter over a finite time window to approximate steady-state behavior and compute well-performing steady-state observer gains. To assess the performance of the proposed solution, simulation results are detailed for the practical case of a formation of Autonomous Underwater Vehicles (AUVs).

关键词： discrete-time Kalman filters Observers State estimation Distribute vehicle filter design Time windows Steady state Autonomous underwater vehicles space vehicle system Launching vehicle systems

3D point cloud downsampling for 2D indoor scene modelling in mobile robotics

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3D point cloud downsampling for 2D indoor scene modelling in...

IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Luís Garrote José Rosa João Paulo Cristiano Premebida Paulo Peixoto Urbano J. Nunes Institute of Systems and Robotics Electrical and Computer Engineering Department University of Coimbra Coimbra Portugal Universidade de Coimbra Coimbra Coimbra PT

Sensory perception and environment modelling are important for autonomous navigation in mobile robotics. 2D discrete grid representations such as the classic 2D occupancy grid maps are a widely used technique in scene representation because of the inherent simplicity and compact representation. In recent years, many 2.5D and 3D grid-based methods have been proposed however, as for the 2D case, a compromise between keeping a low computational bound and reliable sensor interpretation must be kept in order to perform real-world tasks. Assuming the input data in the form of a 3D point-cloud, in this paper we propose a 2D scene modelling approach which converts the 3D data to a 2.5D representation and then to a 2D grid map in an efficient and meaningful manner. The proposed approach incorporates a new rapidly exploring random tree inspired ground-plane detection (RRT-GPD), and an inverse sensor model (ISM) to correctly map 3D to 2.5D and then to 2D grid cells. Experiments were conducted in indoor scenarios with a robotic walker platform equipped with a Microsoft's Kinect One and a LeddarTech's Leddar IS16 sensor. Reported results show an improvement on the representation of non-trivial obstacles (stairs, floor outlets) over a ROS package solution, when applied to a 3D point cloud input.

关键词： Three-dimensional displays Two dimensional displays Robot sensing systems Solid modeling Computational modeling Mobile communication

Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy

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arXiv 2018年

作者： Varatharajah, Yogatheesan Berry, Brent Cimbalnik, Jan Kremen, Vaclav van Gompel, Jamie Stead, Matt Brinkmann, Benjamin Iyer, Ravishankar Worrell, Gregory Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States Mayo Systems Electrophysiology Laboratory Department of Neurology Mayo Clinic RochesterMN55905 United States Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6166 36 Czech Republic Department of Neurosurgery Mayo Clinic RochesterMN55905 United States Department of Physiology & Biomedical Engineering Mayo Clinic RochesterMN55905 United States

An ability to map seizure-generating brain tissue, i.e., the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between ninety minutes and two hours are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

关键词： Support vector machines

Deep EndoVO: A recurrent convolutional neural network (RCNN) based visual odometry approach for endoscopic capsule robots

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arXiv 2017年

作者： Turan, Mehmet Almalioglu, Yasin Araujo, Helder Konukoglu, Ender Sitti, Metin Physical Intelligence Department Max Planck Institute for Intelligent Systems Germany Computer Engineering Department Bogazici Univesity Turkey Institute for Systems and Robotics Universidade de Coimbra Portugal Computer Vision Laboratory Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Medical device companies and many research groups have recently made substantial progresses in converting passive capsule endoscopes to active capsule robots, enabling more accurate, precise, and intuitive detection of the location and size of the diseased areas. Since a reliable real time pose estimation functionality is crucial for actively controlled endoscopic capsule robots, in this study, we propose a monocular visual odometry (VO) method for endoscopic capsule robot operations. Our method lies on the application of the deep Recurrent Convolutional Neural Networks (RCNNs) for the visual odometry task, where Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) are used for the feature extraction and inference of dynamics across the frames, respectively. Detailed analyses and evaluations made on a real pig stomach dataset proves that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories. Copyright © 2017, The Authors. All rights reserved.

关键词： Vision

Non-uniform time-scaling of carnatic music transients

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arXiv 2017年

作者： Viraraghavan, Venkata Subramanian Pal, Arpan Aravind, R. Murthy, Hema TCS Research and Innovation Embedded Systems and Robotics Bangalore India Department of Electrical Engineering Indian Institute of Technology Madras Singapore Department of Computer Science and Engineering Indian Institute of Technology Madras India

Gamakas are an integral aspect of Carnatic Music, a form of classical music prevalent in South India. They are used in rāgas, which may be seen as melodic scales and/or a set of characteristic melodic phrases. Gamakas exhibit continuous pitch variation often spanning several semitones. In this paper, we study how gamakas scale with tempo and propose a novel approach to change the tempo of Carnatic music pieces. The music signal is viewed as consisting of constant-pitch segments and transients. The transients show continuous pitch variation and we consider their analyses from a theoretical stand-point. We next observe the non-uniform ratios of time-scaling of constantpitch segments, transients and silence in excerpts from nine concert renditions of varn. ams in six rāgas. The results indicate that the changing tempo of Carnatic music does not change the duration of transients significantly. We report listening tests on our algorithm to slow down Carnatic music that is consistent with this observation. Copyright © 2017, The Authors. All rights reserved.

关键词： Music

EndoSensorFusion: Particle filtering-based multi-sensory data fusion with switching state-space model for endoscopic capsule robots

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arXiv 2017年

作者： Turan, Mehmet Almalioglu, Yasin Gilbert, Hunter Araujo, Helder Cemgil, Taylan Sitti, Metin Physical Intelligence Department Max Planck Institute for Intelligent Systems Department of Information Technology and Electrical Engineering Eth Zurich Computer Engineering Department Bogazici Univesity Mechanical Engineering Department Louisiana State University Baton RougeLA70803 United States Institute for Systems and Robotics University of Coimbra Computer Engineering Department Bogazici Univesity Physical Intelligence Department Max Planck Institute for Intelligent Systems

A reliable, real time multi-sensor fusion functionality is crucial for localization of actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagnostic and therapeutic technology for the gastrointestinal (GI) tract. In this study, we propose a novel multi-sensor fusion approach based on a particle filter that incorporates an online estimation of sensor reliability and a non-linear kinematic model learned by a recurrent neural network. Our method sequentially estimates the true robot pose from noisy pose observations delivered by multiple sensors. We experimentally test the method using 5 degree-of-freedom (5-DoF) absolute pose measurement by a magnetic localization system and a 6-DoF relative pose measurement by visual odometry. In addition, the proposed method is capable of detecting and handling sensor failures by ignoring corrupted data, providing the robustness expected of a medical device. Detailed analyses and evaluations are presented using ex-vivo experiments on a porcine stomach model prove that our system achieves high translational and rotational accuracies for different types of endoscopic capsule robot trajectories. Copyright © 2017, The Authors. All rights reserved.

关键词： Monte Carlo methods