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GMM Registration: a Probabilistic scan matching approach for sonar-based AUV navigation

GMM Registration: a Probabilistic scan matching approach for...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Pau Vial Miguel Malagón Ricard Segura Narcís Palomeras Marc Carreras Computer Vision and Robotics Research Institute (VICOROB) Universitat de Girona Girona Catalonia

Acoustic perception in underwater environments is challenging due to the low frequency of the acquisition system and multiple and huge sources of noise. Therefore, point clouds built by profiling sonars mounted on Autonomous Underwater Vehicles (AUV) are sparse and noisy. To solve the mapping task, AUVs need a registration algorithm to prevent maps from inconsistencies. Many scan matching algorithms are available, however, a few of them are specialized in acoustic data. In this paper, a probabilistic scan matching methodology based on Gaussian Mixtures Models (GMM) is presented and, for the first time, the Bayesian-GMM algorithm is applied in this context to model acoustic data. The scan matching problem is properly formulated using Lie groups to define pose. In addition, this methodology can return an uncertainty measure for the matching result, which is fundamental in Pose SLAM applications. This tool is implemented in a public C++library 1 1 The library repository can be found in https://***/gmmregistration/gmm_registration. that can process in real-time 2D and 3D scans acquired by a profiling sonar. Theoretical justification and results with real data are provided to benchmark our method against the state-of-the-art Normal Distributions Transforms (NDT) technique.

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Augmented state Kalman filtering for AUV navigation

Augmented state Kalman filtering for AUV navigation

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IEEE International Conference on robotics and Automation (ICRA)

作者： R. Garcia J. Puig P. Ridao X. Cufi Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

Addresses the problem of estimating the motion of an autonomous underwater vehicle (AUV), while it constructs a visual map ("mosaic" image) of the ocean floor. The vehicle is equipped with a down-looking camera which is used to compute its motion with respect to the seafloor. As the mosaic increases in size, a systematic bias is introduced in the alignment of the images which form the mosaic. Therefore, this accumulative error produces a drift in the estimation of the position of the vehicle. When the arbitrary trajectory of the AUV crosses over itself, it is possible to reduce this propagation of image alignment errors within the mosaic. A Kalman filter with augmented state is proposed to optimally estimate both the visual map and the vehicle position.

关键词： Kalman filters Filtering Navigation Motion estimation Underwater vehicles Oceans Remotely operated vehicles Cameras Sea floor State estimation

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A system to evaluate the accuracy of a visual mosaicking methodology

A system to evaluate the accuracy of a visual mosaicking met...

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OCEANS

作者： R. Garcia J. Batlle X. Cufi Institute of Informatics and Applications Computer Vision and Robotics Group University of Girona Girona Spain

When underwater vehicles navigate close to the ocean floor, computer vision techniques can be applied to obtain motion estimates. A complete system to create visual mosaics of the seabed is described in this paper. Unfortunately, the accuracy of the constructed mosaic is difficult to evaluate. The use of a laboratory setup to obtain an accurate error measurement is proposed. The system consists on a robot arm carrying a downward looking camera. A pattern formed by a white background and a matrix of black dots uniformly distributed along the surveyed scene is used to find the exact image registration parameters. When the robot executes a trajectory (simulating the motion of a submersible), an image sequence is acquired by the camera. The estimated motion computed from the encoders of the robot is refined by detecting, to subpixel accuracy, the black dots of the image sequence, and computing the 2D projective transform which relates two consecutive images. The pattern is then substituted by a poster of the sea floor and the trajectory is executed again, acquiring the image sequence used to test the accuracy of the mosaicking system.

关键词： Image sequences Underwater vehicles Motion estimation Robot vision systems Cameras Navigation Oceans computer vision Laboratories computer errors

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Estimating the motion of an underwater robot from a monocular image sequence

Estimating the motion of an underwater robot from a monocula...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Garcia X. Cufi M. Carreras Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot.

关键词： Motion estimation Robots Navigation Underwater vehicles Oceans Floors computer vision Motion detection Vehicle detection Image analysis

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Use of decision trees in colour feature selection. Application to object recognition in outdoor scenes

Use of decision trees in colour feature selection. Applicati...

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IEEE International Conference on Image Processing

作者： J. Freixenet X. Llado J. Marti X. Cufi Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Catalonia Spain

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported.

关键词： Decision trees Object recognition Layout Application software Geometry computer vision Robot vision systems robotics and automation Informatics Concrete

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Towards a real-time vision-based navigation system for a small-class UUV

Towards a real-time vision-based navigation system for a sma...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： R. Garcia T. Nicosevici P. Ridao D. Ribas Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Spain

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory.

关键词： Real time systems Motion estimation Underwater vehicles Sea measurements Position measurement Dead reckoning Sonar navigation Robot vision systems Hydrodynamics Costs

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Omnidirectional depth computation from a single image

Omnidirectional depth computation from a single image

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2005 IEEE International Conference on robotics and Automation

作者： Orghidan, Radu Mouaddib, El Mustapha Salvi, Joaquim Centre de Robotique Electrotechnique et d'Automatique Université de Picardie Jules Verne Amiens France Computer Vision and Robotics Group Institute of Informatics and Applications University of Girona Girona Catalonia Spain

ISBN: (纸本)078038914X

Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications. © 2005 IEEE.

关键词： Cameras

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An approach to vision-based station keeping for an unmanned underwater vehicle

An approach to vision-based station keeping for an unmanned ...

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IEEE International Workshop on Intelligent Robots and Systems (IROS)

作者： X. Cufi R. Garcia P. Ridao Computer Vision and Robotics Group Institute oflnformatics and Applications University of Girona Girona Spain

This paper presents an automatic vision-based system for UUV station keeping. The vehicle is equipped with a down-looking camera, which provides images of the sea-floor. The station keeping system is based on a feature-based motion detection algorithm, which exploits standard correlation and explicit textural analysis to solve the correspondence problem. A visual map of the area surveyed by the vehicle is constructed to increase the flexibility of the system, allowing the vehicle to position itself when it has lost the reference image. The testing platform is the URIS underwater vehicle. Experimental results demonstrating the behavior of the system on a real environment are presented.

关键词： Underwater vehicles Cameras Remotely operated vehicles Motion estimation computer vision Motion detection Robot vision systems Testing Vehicle detection Sea floor

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Robot homing based on corner tracking in a sequence of panoramic images

Robot homing based on corner tracking in a sequence of panor...

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Conference on computer vision and Pattern Recognition (CVPR)

作者： A.A. Argyros K.E. Bekris S.C. Orphanoudakis Computer Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology Hellas FORTH Crete Greece

ISBN: (纸本)0769512720

In robotics, homing can be defined as that behavior which enables a robot to return to its initial (home) position, after traveling a certain distance along an arbitrary path. Odometry has traditionally been used for the implementation of such a behavior, but it has been shown to be an unreliable source of information. In this work, a novel method for visual homing is proposed, based on a panoramic camera. As the robot departs from its initial position, it tracks characteristic features of the environment (corners). As soon as homing is activated, the robot selects intermediate target positions on the original path. These intermediate positions (IPs) are then visited sequentially, until the home position is reached. For the robot to move between two consecutive IPs, it is only required to establish correspondence among at least three corners. This correspondence is obtained through a feature tracking mechanism. The proposed homing scheme is based on the extraction of very low-level sensory information, namely the bearing angles of corners, and has been implemented on a robotic platform. Experimental results show that the proposed scheme achieves homing with a remarkable accuracy, which is not affected by the distance traveled by the robot.

关键词： Robot kinematics Robot sensing systems Insects Robot vision systems Navigation Orbital robotics computer vision Laboratories computer science Information resources

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Real-Time Human Motion Analysis by Image Skeletonization

Real-Time Human Motion Analysis by Image Skeletonization

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作者： Fujiyoshi, Hironobu Lipton, Alan J. Kanade, Takeo Department of Computer Science Chubu University Kasugai-shi 487-8501 Japan Diamondback Vision Inc. Reston VA United States Robotics Institute Carnegie Mellon University Pittsburgh PA United States

In this paper, a process is described for analysing the motion of a human target in a video stream. Moving targets are detected and their boundaries extracted. From these, a "star" skeleton is produced. Two motion cues are determined from this skeletonization: body posture, and cyclic motion of skeleton segments. These cues are used to determine human activities such as walking or running, and even potentially, the target's gait. Unlike other methods, this does not require an a priori human model, or a large number of "pixels on target". Furthermore, it is computationally inexpensive, and thus ideal for real-world video applications such as outdoor video surveillance.

关键词： Real time systems

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