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We introduce Convolutional Neural Support Vector Machines (CNSVMs), a combination of two heterogeneous supervised classification techniques, Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs). CNSVMs are trained using a Stochastic Gradient Descent approach, that provides the computational capability of online incremental learning and is robust for typical learning scenarios in...
We extend a recent low cost real-time method of hand tracking and pose estimation in order to control an anthropomorphic robot hand. The approach is data-driven and based on matching the current image of a color-gloved hand with the best fitting image in a database to retrieve the posture. Then, using depth information from a Kinect camera and a color-sensitive iterative closest point-to-triangle...
We analyze portfolio creation techniques in a high frequency trading domain and randomly changing environments. We aim to create the best risk/reward portfolio based on thousands of profit histories of automated trading robots. We show that the effectiveness of standard portfolio weight calculation rules depends on the dimensionality, N, and the sample size, L, ratio. To resolve dimensionality / sample...
Localization of a mobile robot is a very important issue for robot's navigation. However, localization method with conventional wheel odometry has limits in case the wheel faces slippery conditions. As an alternative way, visual odometry has been researched continuously. However, this method alone has also difficulty for robust localization because wrong depth measurement can frequently occur and...
In this paper, we address the problem of estimating rigid body transformations in two-dimensional space. A new probabilistic weight function is proposed to find a solution closes to odometry information more preferably. The weight function is motivated by hypothesis that a solution of a scan matching problem which prefers odometry information may show better performance in terms of accuracy and convergence...
Recently, it has been researched to adopt the dual arm robot at the packaging and assembly line of an electric device such as a mobile phone. At the research area of the end-effector development, it is necessary to extract demanded functions and to allocate these functions to allowable numbers of end-of-arm-tool (EOAT). On allocating steps, it is often occurred that one EOAT must grip materials with...
The ability to find similar features between two distinct views of the same scene (feature matching) is essential in robotics and computer vision. We are here interested in the robotic-assisted minimally-invasive surgical scenario, for which feature matching can be used to recover tracked features after prolonged occlusions, strong illumination changes, image clutter, or fast camera motion. In this...
An incremental clustering technique to partition 3D point clouds into planar regions is presented in this paper. The algorithm works in real-time on unknown and noisy data, without any initial assumption. An iterative cluster growing technique is proposed in order to correctly classify a flow of 3D points and to merge close regions. The computational efficiency of the approach is achieved by using...
In this paper we propose the integration of an online audio beat tracking system into the general framework of robot audition, to enable its application in musically-interactive robotic scenarios. To this purpose, we introduced a staterecovery mechanism into our beat tracking algorithm, for handling continuous musical stimuli, and applied different multi-channel preprocessing algorithms (e.g., beamforming,...
Recent work in terrain classification has relied largely on 3D sensing methods and color based classification. We present an approach that works with a single, compact camera and maintains high classification rates that are robust to changes in illumination. Terrain is classified using a bag of visual words (BOVW) created from speeded up robust features (SURF) with a support vector machine (SVM) classifier...
In this paper, we present a monocular, texture-based method for person detection and upper-body orientation classification. We build on a commonly used approach for person recognition that uses a Support Vector Machine (SVM) on Histograms of Oriented Gradients (HOG) [1] but replace the SVM by a decision tree with SVMs as binary decision makers. Thereby, in addition to the pure detection of persons,...
Flexible robot assistants allow reducing the costs of acquisition for the automation of small lot sizes in industrial assembly. To additionally decrease the cost for initial start-up and to reach profitability, new concepts for programming these systems are needed. This work describes an approach for a human-machine-interface that enables operators without expert knowledge to commission complex assembly...
In this paper, a local discontinuous Galerkin(LDG) method is designed for solving the Schrödinger equation with three-order spatial derivatives. Our schemes extend the previous work of Xu and Shu [8] on solving the nonlinear Schrödinger equations on LDG method. The L2 stability of the LDG methods is proved for general solutions. Numerical results are shown to illustrate the accuracy and capability...
Computed tomography (CT) has unconquerable advantage over other imaging techniques for detecting lung nodules. The size and the growth rate of lung nodules are the most important indicators for the maglignancy of a lung cancer. Therefore, the accurate segmentation of the lung nodules is of great significance for the diagnosis of the lung cancers. In this paper, we propose a novel method for the segmentation...
In this paper, we present different combined clustering methods and we evaluate their performances and their results on a dataset with ground truth. This dataset, built from several sources, contains a scientific social network in which textual data is associated to each vertex and the classes are known. Indeed, while the clustering task is widely studied both in graph clustering and in non supervised...
If the clustering task is widely studied both in graph clustering and in non supervised learning, combined clustering which exploits simultaneously the relationships between the vertices and attributes describing them, is quite new. In this paper, we present different scenarios for this task and, we evaluate their performances and their results on a dataset, with ground truth, built from several sources...
This paper proposes a hybrid microassembly technique for massively parallel assembly of 200μm × 200μm × 30μm SU-8 chips. The hybrid microassembly technique combines the robotic pick-and-place technique and water mist induced self-assembly technique. The robotic handling tool is used to place microchips roughly on chips of the same size at a fast speed, and then water mist composed of microscopic droplets...
This paper studies the centralized soccer robot vision subsystem, first it introduces the work process of vision subsystem, second it puts forward research method on goal search algorithm, and designs new methods of the dynamic window and color index table combination, the methods solve weaknesses that the target is searched slowly and lost easily, and improve the system robustness.
The voice interface is a big role in the human robot interaction. However, there are problems; imperfectness, deterioration from unknown words, and so on. In order to compensate imperfectness, the proposed robot behaves familiarly like an infant. For the unknown words, the robot learns user-defined voice instructions by the remote controller trigger. The experimental results show that the proposed...
To improve the positioning accuracy of the vision system for apple-picking robot, a method characterized by a marker to recover the spatial location of the apple is proposed. Then the spatial location of the apple obtained with the stem as the matched point is accomplished to get its corresponding depth value of different working distances. Finally, the measured distance with the marker is as a reference...
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