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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Sirvan Khalighi Teresa Sousa Dulce Oliveira Gabriel Pires Urbano Nunes Institute for Systems and Robotics (ISR-UC) University of Coimbra

ISBN: (纸本)9781424441211

In this paper, a novel algorithm is proposed with application in sleep/awake detection and in multiclass sleep stage classification (awake, non rapid eye movement (NREM) sleep and REM sleep). In turn, NREM is further divided into three stages denoted here by S1, S2, and S3. Six electroencephalographic (EEG) and two electro-oculographic (EOG) channels were used in this study. The maximum overlap discrete wavelet transform (MODWT) with the multi-resolution Analysis is applied to extract relevant features from EEG and EOG signals. The extracted feature set is transformed and normalized to reduce the effect of extreme values of features. A set of significant features are selected by mRMR which is a powerful feature selection method. Finally the selected feature set is classified using support vector machines (SVMs). The system achieved 95.0% of average accuracy for sleep/awake detection. As concerns the multiclass case, the average accuracy of sleep stages classification was 93.0%.

关键词： Feature extraction Sleep Stages Support Vector Network discrete wavelet transform wavelet transforms Electrooculography extremum values Electroencephalography Sleep (REM) multi-class

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SLAM for an AUV using vision and an acoustic beacon

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IFAC Proceedings Volumes 2010年第16期43卷 503-508页

作者： M. Bayat A. Pedro Aguiar Institute for Systems and Robotics (ISR) Instituto Superior Técnico (IST) Lisbon Portugal

The estimation of the position and attitude of an autonomous underwater vehicle (AUV) is a challenging and important problem in marine robotics. It is well known that the underwater environment posses considerable problems, that include i) the fact that there is no GPS signal, ii) the communication is usually done through acoustic signals, which suffers from faults, delays and low bandwidth, and iii) the use of vision and/or laser is very limited due to poor visibility. In this paper, we combine a multiple set of sensors to address the full state 6DOF pose estimation of an AUV. The problem is formulated assuming that we have partial measurements from an Inertial Measurement Unit (IMU), an acoustic ranging from a single beacon buoy, and a monocular camera attached to the AUV. Using multiple model estimation techniques and the concept of Extended Kalman Filters with Simultaneous Localization and Mapping (EKF-SLAM), we propose an algorithm that integrates the AUV measurements (that arrive at different sampling-times) and compute in real time an estimate of the position and attitude of the AUV. Simulation results are presented and discussed.

关键词： Underwater Vision IMU Extended Kalman Filter Multiple Model Adaptive Estimator Simultaneous Localization And Mapping Pose Estimation

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Visual Behaviors for Real-Time Control of a Binocular Active Vision System

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IFAC Proceedings Volumes 1997年第3期30卷 167-172页

作者： Jorge Batista Paulo Peixoto Helder Araújo ISR - Institute of Systems and Robotics Department of Electrical Engineering - FCTUC University of Coimbra Portugal

An active vision system has to enable the implementation of reactive visual processes and of elementary visual behaviors in real time. Therefore the control architecture is extremely important. In this paper we discuss a number of issues related with the implementation of a real-time control architecture and describe the architecture we are using with our camera heads. Even though in most applications a fully calibrated system is not required, we also describe a methodology for calibrating the camera head, taking advantage of its degrees of freedom. These calibration parameters are used to evaluate the performance of the system. Another important issue of the operation of active vision binocular heads is their integration into more complex robotic systems. We claim that higher levels of autonomy and integration can be obtained by designing the system architecture based on the concept of purposive behavior. At the lower levels we consider vision as a sensor and integrate it in control systems (both feed-forward and servo loops) and several visual processes are implemented in parallel, computing relevant measures for the control process. At higher levels the architecture is modeled as a state transition system. Finally we show how this architecture can be used to implement a pursuit behavior using optical flow. Simultaneously vergence control can also be performed using the same visual processes.

关键词： Active Vision Real-Time Tracking Smooth-Pursuit

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Trajectory recovery and 3D mapping from rotation-compensated imagery for an airship

Trajectory recovery and 3D mapping from rotation-compensated...

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2007 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Luiz G. B. Mirisola Jorge Dias A. Traca de Almeida ISR-Institute of Systems and Robotics University of Coimbra Portugal

On this paper, inertial orientation measurements are exploited to compensate the rotational degrees of freedom for an aerial vehicle carrying a perspective camera, taking a sequence of images of the ground plane. It is known that, on the pure translation case, full homographies are reduced to planar homologies, and the relative scene depth of two points equals the reciprocal ratio of their image distances to the the FOE. The first part of this paper covers trajectory recovery for an airship carrying a perspective camera taking a sequence of images of the ground plane, as a series of relative poses between successive camera poses. This is commonly named "visual odometry". Previous results showed that the ratio of heights over the ground plane on two views can be calculated more accurately, and thus the altitude component of the trajectory, and here these results are extended by recovering the full 3D camera trajectory. In the second part, the same rotation-compensated imagery is exploited on the mapping domain: from pixel correspondences between successive images the height of points over the ground plane can be recovered, and placed on a DEM grid, performing 3D mapping from monocular aerial images. These results may be useful on the SLAM context.

关键词： Trajectory Cameras Position measurement Robot vision systems Layout Pixel Unmanned aerial vehicles Magnetic sensors Calibration Intelligent robots

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Haptic control for steer-by-wire systems

Haptic control for steer-by-wire systems

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IEEE International Workshop on Intelligent Robots and systems (IROS)

作者： N. Bajcinca R. Cortesao M. Hauschild J. Bals G. Hirzinger Institute of Robotics and Mechatronics DLR Germany Institute of Systems and Robotics ISR Coimbra Portugal

A force-feedback actuation loop for a steer-by-wire vehicle is developed. It is shown that the performance of this loop can be essentially improved by the introduction of a torque sensor. Model reference based control algorithms based on disturbance observer (DOB) and active observers (AOB) are applied to enhance the robustness vs. non-modelled dynamics and uncertain driver impedance.

关键词： Haptic interfaces Control systems Force control Torque Impedance Actuators Mathematical model Robots Mechatronics Wire

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Cooperative single-beacon multiple AUV navigation under stringent communication bandwidth constraints ⁎

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IFAC-PapersOnLine 2021年第16期54卷 216-223页

作者： Francisco Rego António Pascoal CoLAB +Atlantic and Institute for Systems and Robotics (ISR/IST) LARSyS Instituto Superior Técnico Univ. Lisboa Institute for Systems and Robotics (ISR/IST) LARSyS Instituto Superior Técnico Univ. Lisboa

In this paper we propose a method of cooperative navigation of a fleet of AUVs moving in formation with stringent limitations on the bandwidth of the underlying acoustic communications network. In the methodology proposed, one vehicle is equipped with a DVL and the others are equipped with acoustic modems and range-measuring devices that can only measure ranges to the remaining vehicles in the formation and to an underwater beacon or transponder located at a known position. Based on DVL and range measurements, and through the exchange of information among the vehicles, each vehicle must estimate its own position and the positions of the other vehicles in the fleet. The estimates obtained are then used for geo-referencing purposes as well as formation control. We use methods of distributed and quantised state estimation to solve this problem. We investigate through numerical simulations what type of information should be shared among the vehicles (range measurements or position estimates) for an efficient tradeoff between bandwidth and state estimation performance, which may lead to a better scalability of the formation.

关键词： Co-operative control navigation Autonomous underwater vehicles Adaptive quantization

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Feature extraction for moving objects tracking system in indoor environments

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IFAC Proceedings Volumes 2004年第8期37卷 96-101页

作者： Daniel Castro Urbano Nunes António Ruano Centre for Intelligent Systems - CSI University of Algarve Portugal Institute of Systems and Robotics - ISR University of Coimbra Portugal

In this paper a feature extraction and classification methodology for a laser based detection and tracking of moving objects (DATMO) system in indoors environments is presented. The sensory perception is based in a SICK Laser Measurement System (LMS). An adaptation of the Hough Transform is used in the feature extraction procedure to interpret scanned segments, as primitive features, defined by geometric evidence (points, lines, circles and blobs), and high-level features, generally referred to as landmarks (corners, columns, doors, etc.). The classification system uses features data, some heuristic rules, and data from a Kalman filter based tracking system to classify multiple objects. Real and simulated results are presented to verify the effectiveness of the proposed DATMO system in unknown environments with multiple moving objects.

关键词： Autonomous mobile robots detection algorithms

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Cooperative Motion Control of Multiple Autonomous Marine Vehicles: Collision Avoidance in Dynamic Environments

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IFAC Proceedings Volumes 2010年第16期43卷 395-400页

作者： Sergio Carvalhosa A. Pedro Aguiar A. Pascoal Instituto Superior Tecnico - Institute for Systems and Robotics (IST-ISR) Lisbon 1049-001 Portugal

This paper addresses the problem of cooperative motion control (CMC) of multiple autonomous marine vehicles, taking explicitly into account collision avoidance in dynamic environments. A Collision Avoidance System (CAS) for a CMC architecture is proposed that consists of two subsystems: Collision Prediction and Collision Avoidance. Collision Prediction aims at estimating the most probable trajectory of a given obstacle. To this effect, a bank of Kalman filters are run in parallel, with each filter using a different plausible model for obstacle motion. The most probable model is chosen according to a decision algorithm. Each of the vehicle trajectories is then checked for possible collision with the obstacle. Should the possibility of a collision occur, Collision Avoidance is achieved either by controlling the speed of each vehicle along its assigned path or through path re-planing using harmonic potential fields. Because group coordination must be taken into consideration, collision avoidance is implemented using a decentralized system that is suited for multiple heterogeneous vehicles. The paper summarizes the key concepts and the methodology used to implement a Collision Avoidance System for teams of vehicles. The efficacy of the system is assessed in simulation with dynamic models of a group of marine surface craft using NetMarSys, a Cooperative Motion Control Simulator developed at isr/IST.

关键词： Cooperative Motion Control Collision Avoidance Collision Prediction Autonomous Marine Vehicles Potential field theory Kalman filtering

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Experimental Evaluation of a Novel Webcam-Based Tachometer for In-Situ Rotational Speed Measurement

Experimental Evaluation of a Novel Webcam-Based Tachometer f...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Fernando J.T.E. Ferreira André F.F. Duarte Fernando J.P. Lopes Institute of Systems and Robotics (ISR) University of Coimbra Coimbra Portugal

ISBN: (数字)9781728157542

ISBN: (纸本)9781728157559

Rotational speed measurement of industrial rotating machinery and mechanical parts is of great interest for process and system monitoring and control, process characterization and fault diagnosis. The estimation of motor load and pulley-belt transmission slip in induction motor driven systems are examples where the rotational speed measurement can be useful. In conventional systems, mechanical coupling of devices such as encoders and resolvers with the rotating shaft/part is required for continuous speed measurement. For short-time measurements, optical reflection or stroboscopic techniques can be used through noninvasive contactless optical tachometers. Reflective marks or strips in the rotating parts are usually required when using optical tachometers. In this paper, the results of several experimental tests under different light sources for an innovative nonintrusive, low-cost, webcam-based tachometer, previously proposed by the authors, are presented and discussed. For a motor shaft speed varying between 750 and 3000 rpm, the average error obtained with the proposed solution was lower than 0.2%. Such solution can be used to continuously measure the speed of a given rotating part during an in-situ energy audit or operation characterization period, with real-time data logging and without sticking reflective strips or introducing shaft-coupled encoders/resolvers, allowing the speed to be easily estimated/measured and recorded over time in, for example, electrical motors, pulleys, shafts and wind turbines.

关键词： Velocity control Rotation measurement Tachometers Induction motors Cameras Velocity measurement Sensors

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Bayesian 3D independent motion segmentation with IMU-aided RBG-D sensor

Bayesian 3D independent motion segmentation with IMU-aided R...

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International Conference on Multisensor Fusion and Integration for Intelligent systems (MFI)

作者： Jorge Lobo João Filipe Ferreira Pedro Trindade Jorge Dias Institute of Systems and Robotics (ISR) and the Department of Electrical and ComputerEngineering University of Coimbra Portugal ISR-Institute of Systems and Robotics University of Coimbra Portugal Robotics Institute Khalifa University Abu Dhabi UAE

In this paper we propose a two-tiered hierarchical Bayesian model to estimate the location of objects moving independently from the observer. Biological vision systems are very successful in motion segmentation, since they efficiently resort to flow analysis and accumulated prior knowledge of the 3D structure of the scene. Artificial perception systems may also build 3D structure maps and use optical flow to provide cues for ego- and independent motion segmentation. Using inertial and magnetic sensors and an image and depth sensor (RGB-D) we propose a method to obtain registered 3D maps, which are subsequently used in a probabilistic model (the bottom tier of the hierarchy) that performs background subtraction across several frames to provide a prior on moving objects. The egomotion of the RGB-D sensor is estimated starting with the angular pose obtained from the filtered accelerometers and magnetic data. The translation is derived from matched points across the images and corresponding 3D points in the rotation-compensated depth maps. A gyro-aided Lucas Kanade tracker is used to obtain matched points across the images. The tracked points can also used to refine the initial sensor based rotation estimation. Having determined the camera egomotion, the estimated optical flow assuming a static scene can be compared with the observed optical flow via a probabilistic model (the top tier of the hierarchy), using the results of the background subtraction process as a prior, in order to identify volumes with independent motion in the corresponding 3D point cloud. To deal with the computational load CUDA-based solutions on GPUs were used. Experimental results are presented showing the validity of the proposed approach.

关键词： Optical imaging Robot sensing systems Optical sensors Cameras Motion segmentation Computer vision Observers

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