14 research outputs found

    Towards binocular active vision in a robot head system

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    This paper presents the first results of an investigation and pilot study into an active, binocular vision system that combines binocular vergence, object recognition and attention control in a unified framework. The prototype developed is capable of identifying, targeting, verging on and recognizing objects in a highly-cluttered scene without the need for calibration or other knowledge of the camera geometry. This is achieved by implementing all image analysis in a symbolic space without creating explicit pixel-space maps. The system structure is based on the ‘searchlight metaphor’ of biological systems. We present results of a first pilot investigation that yield a maximum vergence error of 6.4 pixels, while seven of nine known objects were recognized in a high-cluttered environment. Finally a “stepping stone” visual search strategy was demonstrated, taking a total of 40 saccades to find two known objects in the workspace, neither of which appeared simultaneously within the Field of View resulting from any individual saccade

    Clifford algebra with mathematica

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    The Clifford algebra of a n-dimensional Euclidean vector space provides a general language comprising vectors, complex numbers, quaternions, Grassman algebra, Pauli and Dirac matrices. In this work, we present an introduction to the main ideas of Clifford algebra, with the main goal to develop a package for Clifford algebra calculations for the computer algebra program Mathematica. The Clifford algebra package is thus a powerful tool since it allows the manipulation of all Clifford mathematical objects. The package also provides a visualization tool for elements of Clifford Algebra in the 3-dimensional space

    Autonomous clothes manipulation using a hierarchical vision architecture

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    This paper presents a novel robot vision architecture for perceiving generic 3-D clothes configurations. Our architecture is hierarchically structured, starting from low-level curvature features to mid-level geometric shapes and topology descriptions, and finally, high-level semantic surface descriptions. We demonstrate our robot vision architecture in a customized dual-arm industrial robot with our inhouse developed stereo vision system, carrying out autonomous grasping and dual-arm flattening. The experimental results show the effectiveness of the proposed dual-arm flattening using the stereo vision system compared with the single-arm flattening using the widely cited Kinect-like sensor as the baseline. In addition, the proposed grasping approach achieves satisfactory performance when grasping various kind of garments, verifying the capability of the proposed visual perception architecture to be adapted to more than one clothing manipulation tasks

    Continuous perception for deformable objects understanding

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    We present a robot vision approach to deformable object classification, with direct application to autonomous service robots. Our approach is based on the assumption that continuous perception provides robots with greater visual competence for deformable objects interpretation and classification. Our approach thus classifies the category of clothing items by continuously perceiving the dynamic interactions of the garment’s material and shape as it is being picked up. Our proposed solution consists of extracting continuously visual features of a RGB-D video sequence and fusing features by means of the Locality Constrained Group Sparse Representation (LGSR) algorithm. To evaluate the performance of our approach, we created a fully annotated database featuring 150 garment videos in random configurations. Experiments demonstrate that by continuously observing an object deform, our approach achieves a classification score of 66.7%, outperforming state-of-the-art approaches by a ∌ 27.3% increase

    Unsupervised clustering in Hough space for recognition of multiple instances of the same object in a cluttered scene

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    We describe an active binocular vision system that is capable of localising multiple instances of objects of the same-class in different settings within a covert, pre-attentive, visual search strategy. By clustering SIFT-feature matches that have been projected into a non-quantised (i.e. continuous) Hough space we are able to detect up to 6 same-class object instances simultaneously while tolerating up to ∼ 66% of each object’s surface being occluded by another object instance of the same-class. Our findings are based on using a database of ∼ 2300 images of synthetically composited and real-world images

    A Heuristic-Based Approach for Flattening Wrinkled Clothes

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    Towards a unified visual framework in a binocular active robot vision system

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    This paper presents the results of an investigation and pilot study into an active binocular vision system that combines binocular vergence, object recognition and attention control in a unified framework. The prototype developed is capable of identifying, targeting, verging on and recognising objects in a cluttered scene without the need for calibration or other knowledge of the camera geometry. This is achieved by implementing all image analysis in a symbolic space without creating explicit pixel-space maps. The system structure is based on the ‘searchlight metaphor’ of biological systems. We present results of an investigation that yield a maximum vergence error of ~6.5 pixels, while 85% of known objects were recognised in five different cluttered scenes. Finally a ‘stepping-stone’ visual search strategy was demonstrated, taking a total of 40 saccades to find two known objects in the workspace, neither of which appeared simultaneously within the field of view resulting from any individual saccade

    Experimental determination of the flow capacity coefficient for control valves of process

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    A test bench was conceived in order to determine experimentally the flow coefficient [CV] for process control valves, operating with compressible fluids, under established regulations by the standards ANSI/ISA-75.02-1996 and ANSI/ISA-75.01.01-2002. This test bench is used to verify the calibration of valves with continually variable opening, after they have been repaired. The measurements in the test bench allow establishing the CV of these valves for various opening percentages. It was necessary to go through the CV equation for compressible fluids, to proceed with the flow sensor selection. This equation was obtained under similarity conditions by the equality of Euler numbers between prototype and model (test specimen). It is also described the electronic instrumentation for measuring flow, temperature and pressure difference, the design and the development of electronic circuits which control the instrumentation, and the algorithms for the operation and acquisition of measurements
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