intelligent autonomous mobile robots must be able to sense and recognize 3D indoor space where they live or work. In this paper, we propose a new 3D sensing system using the laser structured lighting method, because o...
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ISBN:
(纸本)0780384636
intelligent autonomous mobile robots must be able to sense and recognize 3D indoor space where they live or work. In this paper, we propose a new 3D sensing system using the laser structured lighting method, because of its robustness on the nature of the navigation environment and the easy extraction of feature information of interest. The proposed active trinocular vision system is composed of a flexible multi-stripe laser projector and two cameras arranged with a triangular shape. Based on the virtual camera concept and the trinocular epipolar constraints, the matching pairs of line features in two real camera images are established, and 3D information from one-shot image can be extracted on the patterned scene. Especially, for robust line feature matching, we propose a new correspondence matching algorithms based on line grouping and probabilistic voting. Finally, a series of experimental tests is performed to show its efficiency and accuracy.
This paper describes a novel application of active learning techniques in the field of robotic grasping. A vision-based grasping system has been implemented on a humanoid robot. It is able to compute a set of feasible...
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ISBN:
(纸本)9781586034528
This paper describes a novel application of active learning techniques in the field of robotic grasping. A vision-based grasping system has been implemented on a humanoid robot. It is able to compute a set of feasible grasps and to execute any of them and measure their actual reliability. An algorithm aimed at predicting the performance of an untested grasp using the results observed on previous similar attempts is presented. The previous experience is stored using a set of vision-based grasp descriptors. Moreover, a second algorithm that actively selects the next grasp to be executed in order to improve the predictive quality of the accumulated experience is introduced. An exhaustive database of experimental data is collected and used to test and validate both algorithms.
Motion vision (visual odometry, the estimation of camera egomotion) is a well researched field, yet has seen relatively limited use despite strong evidence from biological systems that vision can be extremely valuable...
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Motion vision (visual odometry, the estimation of camera egomotion) is a well researched field, yet has seen relatively limited use despite strong evidence from biological systems that vision can be extremely valuable for navigation. The limited use of such vision techniques has been attributed to a lack of good algorithms and insufficient computer power, but both of those problems were resolved as long as a decade ago. A gap presently yawns between theory and practice, perhaps due to perceptions of robot vision as less reliable and more complex than other types of sensing. We present an experimental methodology for assessing the real world precision and reliability of visual odometry techniques in both normal and extreme terrain. This paper evaluates the performance of a mobile robot equipped with a simple vision system in common outdoor and indoor environments, including grass, pavement, ice, and carpet. Our results show that motion visionalgorithms can be robust and effective, and suggest a number of directions for further development.
Standard bundle adjustment techniques for Euclidean reconstruction consider camera intrinsic parameters as unknowns in the optimization process. Obviously, the speed of an optimization process is directly related to t...
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Standard bundle adjustment techniques for Euclidean reconstruction consider camera intrinsic parameters as unknowns in the optimization process. Obviously, the speed of an optimization process is directly related to the number of unknowns and to the form of the cost function. The scheme proposed in this paper differs from previous standard techniques since unknown camera intrinsic parameters are not considered in the optimization process. Considering fewer unknowns in the optimization process produces a faster algorithm, which is more adapted to time-dependent applications such as robotics. Computationally expensive metric reconstruction, using for example several zooming cameras, considerably benefits from an intrinsics-free bundle adjustment.
Eigendecomposition is a common technique that is performed on sets of correlated images in a number of computervision and robotics applications. Unfortunately, the computation of an eigendecomposition can become proh...
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Eigendecomposition is a common technique that is performed on sets of correlated images in a number of computervision and robotics applications. Unfortunately, the computation of an eigendecomposition can become prohibitively expensive when dealing with very high resolution images. While reducing the resolution of the images will reduce the computational expense, it is not known a priori how this will affect the quality of the resulting eigendecomposition. The work presented here provides an analysis of how different resolution reduction techniques affect the eigendecomposition. A computationally efficient algorithm for calculating the eigendecomposition based on this analysis is proposed. Examples show that this algorithm performs very well on arbitrary video sequences.
The proceedings contains 33 papers from the conference on SPIE - intelligentrobots and computervision XXI: algorithms, techniques, and active vision. The topics discussed include: learning for intelligent mobile rob...
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The proceedings contains 33 papers from the conference on SPIE - intelligentrobots and computervision XXI: algorithms, techniques, and active vision. The topics discussed include: learning for intelligent mobile robots;remote operation of robotics systems using WLAN- and CORBA-based architecture;autonomous cross-country driving using activevision;Web-based telerobotics system in a virtual reality environment;automatic calibration and neural networks for robot guidance;recursive least squares approach to calculate motion parameters for a moving camera;and effective color representation for image segmentation under nonwhite illumination.
Many computervision applications can benefit from omnidirectional vision sensing, rather than depending solely on conventional cameras that have constrained fields of view. For example, mobile robots often require a ...
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Many computervision applications can benefit from omnidirectional vision sensing, rather than depending solely on conventional cameras that have constrained fields of view. For example, mobile robots often require a full 360degrees. view of their environment in order to perform navigational tasks such identifying landmarks, localizing within the environment, and determining free paths in which to move. There has been much research interest in omnidirectional vision in the past decade and many techniques have been developed. These techniques include: (i) catadioptric methods which can provide rapid image acquisition, but lack image resolution;and (ii) mosaicing and linear scanning techniques which have high image resolution but typically have slow image acquisition speed. In this paper, we introduce a novel linear scanning panoramic vision system that can acquire panoramic images quickly with little loss of image resolution. The system makes use of a fast line-scan camera, instead of a slower, conventional area-scan camera. In addition, a unique coarse-to-fine panoramic imaging technique has been developed that is based on smart sensing principles. Using the activevision paradigm, we control the motion of the rotating camera using feedback from the images. This results in high acquisition speeds and proportionally low storage requirements. Experimentation has been carried out, and results are given.
There has been a great interest in the recent years in visual coordination and target tracking for mobile robots cooperating in unstructured environments. This paper describes visual servo control techniques suitable ...
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ISBN:
(纸本)081945155X
There has been a great interest in the recent years in visual coordination and target tracking for mobile robots cooperating in unstructured environments. This paper describes visual servo control techniques suitable for intelligent task planning of cooperative robots operating in unstructured environment. In this paper, we have considered a team of semi-autonomous robots controlled by a remote supervisory control system. We have presented an algorithm for visual position tracking of individual cooperative robots within their working environment. Initially, we present a technique suitable for visual servoing of a robot toward its landmark targets. Secondly, we present an image-processing technique that utilizes images from a remote surveillance camera for localization of the robots within the operational environment. In this algorithm, the surveillance camera can be either stationary or mobile. The supervisor control system keeps tracks of relative locations of individual robots and utilizes relative coordinate information of the robots to plan their cooperative activities. We presented some results of this research effort that illustrates effectiveness of the proposed algorithms for cooperative robotic systems visual team working and target tracking.
This paper describes the development of a miniature assembly cell for microsystems. The cell utilizes a transparent electrostatic gripper all-owing the use of computervision for part alignment with respect to the gri...
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ISBN:
(纸本)081945155X
This paper describes the development of a miniature assembly cell for microsystems. The cell utilizes a transparent electrostatic gripper all-owing the use of computervision for part alignment with respect to the gripper. Part to assembly alignment is achieved via optical triangulation using a fiber-coupled laser and a position sensitive detector (PSD). The system layout, principle of operation and design are described along with the visual and optical control algorithms and their implementation. Experimental measurements of the performance of the stage indicate normal and tangential gripping forces in the range of 0.03-2.5 mN and 1.-9. mN respectively. The visual search algorithm limits the feature tracking speed to 111ms /search. The alignment accuracy of the visual and optical proportional position feedback controls were determined to be +/-7 mum and +/-10 mum respectively.
The vision evolved not only as a recognition system, but also as a sensory system for reaching, grasping and other motion activities. In advanced creatures, it has become a component of prediction functions, allowing ...
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ISBN:
(纸本)081945155X
The vision evolved not only as a recognition system, but also as a sensory system for reaching, grasping and other motion activities. In advanced creatures, it has become a component of prediction functions, allowing the creation of environmental models and activity planning. Fast information processing and decision making requires reduction of informational and computational complexities. The brain achieves this goal using symbolic coding, hierarchical compression, and selective processing of visual information. Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are the parts of a single mechanism, is the most feasible for such models. It converts visual information into the relational Network-Symbolic structures, instead of precise computations of 3-dimensional models. Narrow foveal vision provides separation of figure from ground, object identification, semantic analysis, and precise control of actions. Rough wide peripheral vision identifies and tracks salient motion, guiding foveal system to salient objects. It also provides scene context. Objects and other stable systems have coherent relational structures. Network-Symbolic transformations derive more abstract structures that allow invariably recognize a particular structure as an exemplar of class. Robotic systems, equipped with such smart vision, will be able to navigate in any environment, understand situation, and act accordingly.
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