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Adaptive path planning for multiple vehicles with bounded curvature 1

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11th Latin-American robotics Symposium on robotics, LARS 2014

作者： Macharet, Douglas G. Campos, Mario F.M. Computer Vision and Robotics Laboratory Computer Science Department Universidade Federal de Minas Gerais Belo Horizonte MG Brazil

ISBN: (数字)9783662481349

ISBN: (纸本)9783662481332

In this paper we introduce the k-Dynamic Dubins TSP with Neighborhoods (k-DDTSPN), the problem consisting of planning efficient paths among a set of target regions dynamically selected in the environment for multiple robots with bounded curvature (Dubins vehicle). We propose a decentralized auction-based technique, which uses a greedy constructive strategy to dynamically calculate the cost of insertion of the new region to each path and selects the one with the minimum impact on the length. We provide a formal analysis of the proposed technique, presenting an upper bound for the length of the longest tour. Several trials were executed in a simulated environment, allowing for a statistical investigation of the results. © Springer-Verlag Berlin Heidelberg 2015.

关键词： Traveling salesman problem

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Human action recognition using 2DPCA-DMM representation and GA-SVM in depth sequences 6

Human action recognition using 2DPCA-DMM representation and ...

引用

6th International Conference on Knowledge and Systems Engineering, KSE 2014

作者： Viet, Vo Hoai Ngoc, Ly Quoc Son, Tran Thai Computer Vision and Robotics Department University of Science - VNU - HCMC Ho Chi Minh Viet Nam

ISBN: (纸本)9783319116792

Automatic human action recognition is an interesting and challenging problem in computer vision. Furthermore, it has wide range of real-world applications such as human-machine interaction, surveillance system, data-driven automation, smart home and robotics. In the recent years, the availability of 3D sensors has recently made it possible to capture depth maps in real time, which simplifies variety of visual recognition tasks, including action classification, 3D reconstruction, etc? We address here the problem of human action recognition in depth sequences. On one hand, we present a novel for human action recognition based on 2DPCA applied to DMM. Then, we project feature matrixes into difference spaces to create robust action representation. Finally, we use GA to create the coefficients for multi- SVM classifiers. Our approach is systematically examined on benchmark datasets such as MSR-Gesture3D and MSR-Action3D which results with an overall accuracy of 91.32% on the MSR-Action3D and 94.89% on the MSR-Gesture3D. The experimental results also indicated that the extraction of features and representation are effective and shows the effective of our proposal. © Springer International Publishing Switzerland 2015.

关键词： Genetic algorithms

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A vision based aerial robot solution for the Mission 7 of the International Aerial robotics Competition

A vision based aerial robot solution for the Mission 7 of th...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Jose Luis Sanchez-Lopez Jesús Pestana Jean-Franois Collumeau Ramon Suarez-Fernandez Pascual Campoy Martin Molina Computer Vision Group Centre for Automation and Robotics Spain Aerial Vision Group Graz University of Technology - TUGraz Austria Robotics Institute Delft University of Technology (TU Delft) Delft The Netherlands Department of Artificial Intelligence Technical University of Madrid (UPM) Spain

ISBN: (纸本)9781479960118

The International Aerial robotics Competition (IARC) aims at pulling forward the state of the art in UAV. The Mission's 7 challenge deals mainly with GPS/Laser denied navigation, Robot-Robot interaction and obstacle avoidance in the setting of a ground robot herding problem. We present in this paper our UAV which took part in the 2014 competition, in the China venue. This year, the mission was not completed by any participant but our team at Technical University of Madrid (UPM) were awarded with two special prizes: Best Target Detection and Best System Control. The platform, hardware and the developed software used in this top leading competition are presented in this paper. This software has three main components: the visual localization and mapping algorithm; the control algorithms; and the mission planner. A statement of the safety measures integrated in the drone and of our efforts to ensure field testing in conditions as close as possible to the challenger's are also included.

关键词： Robots computer architecture Optical sensors Vehicles computers Safety

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Rapid quantification of total polyphenol content in EVOO using NIR sensor with wavelength selection and FS-MLR 12

Rapid quantification of total polyphenol content in EVOO usi...

引用

12th IEEE International Conference on Imaging Systems and Techniques, IST 2015

作者： Martínez Gila, D.M. Beltrán Ortega, J. Gámez García, J.G. Gómez Ortega, J. Robotics Automation and Computer Vision Group University of Jaen Campus Las Lagunillas s/n JaenES-23071 Spain

ISBN: (纸本)9781479986330

Olive oil quality is regulated by an European normative, and according to different chemical and organoleptic markers the olive oil can be labelled as lampante, virgin or extra virgin olive oil (EVOO), being the last the top-quality one. Since these parameters determine mainly the olive oil chemical stability, in the last years different works have studied the favourable influence of others olive oil minor components on the human health. Polyphenols are one of these minor components. This research has been carried out to study the correlation between the polyphenols contained into EVOO and its spectral response in the near infrared. The selection of the best correlated spectral wavelengths could be the first step to build a rapid and low-cost NIR sensor to be set up into the elaboration process in order to control the presence of these components. During the process, several olive oil variables such as temperature, humidity, turbidity.. could affect to the NIR response. In this sense, this work has studied the influence of the olive oil turbidity on the error of polyphenol content prediction. For this study 63 olive oil samples obtained from an olive oil mill have been employed and the reference values were obtained by an external laboratory with chemical analysis. Spectra were filtered with an ANOVA analysis and the best correlated band was identified between 1690 and 1870 nm. The regression algorithm FSMLR was used and it got a RMSECV of 75 ppm, the R2 coefficient was 0.94 and the RPD value was 4.76. The results get worse when samples with different turbidity indexes were used. © 2015 IEEE.

关键词： Olive oil

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Robust face recognition using key-point descriptors 10

Robust face recognition using key-point descriptors

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10th International Conference on computer vision Theory and Applications, VISAPP 2015

作者： Klemm, Soeren Andreu, Yasmina Henriquez, Pedro Matuszewski, Bogdan J. Robotics and Computer Vision Research Laboratory School of Computing Engineering and Physical Sciences University of Central Lancashire Preston United Kingdom

ISBN: (纸本)9789897580901

Key-point based techniques have demonstrated a good performance for recognition of various objects in numerous computer vision applications. This paper investigates the use of some of the most popular key-point descriptors for face recognition. The emphasis is put on the experimental performance evaluation of the key-point based face recognition methods against some of the most popular and best performing techniques, utilising both global (Eigenfaces) and local (LBP, Gabor filters) information extracted from the whole face image. Most of the results reported in literature so far, on the use of the key-points descriptors for the face recognition, concluded that the methods based on processing of the full face image have somewhat better performances than methods using exclusively key-points. The results reported in this paper suggest that the performance of the key-point based methods could be at least comparable to the leading "whole face" methods and are often better suited to handle face recognition in practical applications, as they do not require face image co-registration, and perform well even with significantly occluded faces.

关键词： Face recognition

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Real-time monocular obstacle avoidance using Underwater Dark Channel Prior

Real-time monocular obstacle avoidance using Underwater Dark...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Paulo Drews Emili Hernandez Alberto Elfes Erickson R. Nascimento Mario Campos Autonomous Systems Laboratory Data61-CSIRO Brisbane Australia Computer Vision and Robotics Laboratory of the Dep. de Ciencia da Computacao Univ. Federal de Minas Gerais - UFMG Belo Horizonte Brazil

ISBN: (纸本)9781509037636

In this paper we propose a new vision-based obstacle avoidance strategy using the Underwater Dark Channel Prior (UDCP) that can be applied to any Unmanned Underwater Vehicle (UUV) equipped with a simple monocular camera and minimal on-board processing capabilities. For each incoming image, our method first computes a relative depth map to estimate the obstacles nearby. Then, the map is segmented and the most promising Region of Interest (RoI) is identified. Finally, an escape direction is computed within the RoI and a control action is performed accordingly to avoid the obstacles. We tested our approach on a video sequence in a natural environment and compared it against a state-of-the-art method showing better performance, specially in light changing conditions. We also provide online results on a low-cost Remotely Operated Vehicle (ROV) in a controlled environment.

关键词： Obstacle avoidance control action Video sequences Underwater Collision avoidance Controlled Environment Natural environment monocular camera region of interest

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Free-floating panel intervention by means of learning by demonstration 4

Free-floating panel intervention by means of learning by dem...

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4th IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles, NGCUV 2015

作者： Carrera, Arnau Palomeras, Narcís Hurtós, Natàlia Carreras, Marc Computer Vision and Robotics Institute Centre d'Investigació en Robòtica Submarina Universitat de Girona Girona17003 Spain

Recent efforts in the field of intervention-autonomous underwater vehicles (I-AUVs) have started to show promising results in simple manipulation tasks. However, there is still a long way to go to reach the complexity of the tasks carried out by ROV pilots. This paper proposes an intervention framework based on Learning by Demonstration (LbD) techniques in order to easily acquire the manipulation skills of a pilot and be able to reproduce similar tasks autonomously. We describe the learning algorithm as well as its interplay with the rest of the modules (navigation, perception, control) that take part in the proposed framework. We show results on a free-floating valve turning task, using Girona 500 AUV equipped with a manipulator, a passive gripper, a force/torque sensor, a camera and a haptic device to perform the demonstrations. Obtained results show the feasibility of the LbD algorithm to perform autonomous intervention even under the presence of perturbations. © 2015, IF AG (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Autonomous underwater vehicles

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REFLECTION REMOVAL USING DISPARITY AND GRADIENT-SPARSITY VIA SMOOTHING ALGORITHM

REFLECTION REMOVAL USING DISPARITY AND GRADIENT-SPARSITY VIA...

引用

IEEE International Conference on Image Processing

作者： Tharatch Sirinukulwattana Gyeongmin Choe In So Kweon Robotics and Computer Vision Lab KAIST

ISBN: (纸本)9781479983407

The purpose of this paper is to introduce a new method for removing reflections from multi-view images taken through a transparent medium, such as pane glass. Our method utilizes an optimization approach based on the probabilistic model of relative smoothness algorithm, which exploits gradient value to separate the image into two sub-layers. As this algorithm has certain limitations on removing reflections, we improve upon it by imposing a gradient-sparsity constraint. This allows the type of reflection captured within a camera's focal length to be effectively removed. We also introduce another constraint on a disparity map which smooths specific areas of reflection layer while simultaneously preserves the sharpness of the main object. These two major contributions are proven to be sufficient in producing high-quality images. Our algorithm demonstrates good results compared with other existing methods as most of the reflection spots have been removed, and the computational time of our system is arguably fast.

关键词： Reflection removal Layer separation Reflection reflecting layer smoothing algorithms images Probabilistic Model Sharpness computational time

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Learning a Deep Convolutional Network for Light-Field Image Super-Resolution

Learning a Deep Convolutional Network for Light-Field Image ...

引用

International Conference on computer vision Workshops (ICCV Workshops)

作者： Youngjin Yoon Hae-Gon Jeon Donggeun Yoo Joon-Young Lee In So Kweon Robotics and Computer Vision Lab KAIST

Commercial Light-Field cameras provide spatial and angular information, but its limited resolution becomes an important problem in practical use. In this paper, we present a novel method for Light-Field image super-resolution (SR) via a deep convolutional neural network. Rather than the conventional optimization framework, we adopt a datadriven learning method to simultaneously up-sample the angular resolution as well as the spatial resolution of a Light-Field image. We first augment the spatial resolution of each sub-aperture image to enhance details by a spatial SR network. Then, novel views between the sub-aperture images are generated by an angular super-resolution network. These networks are trained independently but finally finetuned via end-to-end training. The proposed method shows the state-of-the-art performance on HCI synthetic dataset, and is further evaluated by challenging real-world applications including refocusing and depth map estimation.

关键词： Spatial resolution Cameras Lenses Image restoration Neural networks

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DEPTH FROM ACCIDENTAL MOTION USING GEOMETRY PRIOR

DEPTH FROM ACCIDENTAL MOTION USING GEOMETRY PRIOR

引用

IEEE International Conference on Image Processing

作者： Sung-Hoon Im Gyeongmin Choe Hae-Gon Jeon In So Kweon Robotics and Computer Vision Lab KAIST

ISBN: (纸本)9781479983407

We present a method to reconstruct dense 3D points from small camera motion. We begin with estimating sparse 3D points and camera poses by Structure from Motion (SfM) method with homography decomposition. Although the estimated points are optimized via bundle adjustment and gives reliable accuracy, the reconstructed points are sparse because it heavily depends on the extracted features of a scene. To handle this, we propose a depth propagation method using both a color prior from the images and a geometry prior from the initial points. The major benefit of our method is that we can easily handle the regions with similar colors but different depths by using the surface normal estimated from the initial points. We design our depth propagation framework into the cost minimization process. The cost function is linearly designed, which makes our optimization tractable. We demonstrate the effectiveness of our approach by comparing with a conventional method using various real-world examples.

关键词： Structure from motion Small baseline Depth propagation geometry Bundle adjustment surface normal Cost functions minimization process Handles Color

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