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ABSTRACT: Developing easy to use, intuitive interfaces is crucial to introduce robotic automation to many small medium sized enterprises (SMEs). Due to their continuously changing product lines, reprogramming costs exceed installation costs by a large margin. In addition, traditional programming methods for industrial robots is too complex for an inexperienced robot programmer, thus external assistance is often needed. In this paper a new incremental multimodal language, which uses augmented reality (AR) environment, is presented. The proposed language architecture makes it possible to manipulate, pick or place the objects in the scene. This approach shifts the focus of industrial robot programming from coordinate based programming paradigm, to object based programming scheme. This makes it possible for non-experts to program the robot in an intuitive way, without going through rigorous training in robot programming.
Robotics and Automation (ICRA), 2011 IEEE International Conference on; 06/2011
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ABSTRACT: This paper proposes a stereo vision based localization and mapping strategy for vehicular navigation within industrial environments using natural landmarks. The work proposed is strictly related to factory automation, since focus is on industrial vehicle autonomous navigation for material handling, in order to increase the operating efficiency with reduced risk for accidents. The stereovision system, proposed as the main sensor, provides the necessary feedback to navigate and simultaneously calibrate the stereocamera parameters (like the camera separation, focal length, camera placement with respect to the robot, etc.). It uses the natural landmarks already present in the environment without additional infrastructures. Some simulation and experimental results are presented in order to explain the proposed method and current status.
Emerging Technologies & Factory Automation, 2009. ETFA 2009. IEEE Conference on; 10/2009
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ABSTRACT: This paper presents results from experiments on visual stereo matching for robot navigation. Visual features are stereo paired with respect to their pixel position. Stereo triangulating all paired visual features results in a set of landmarks whereof a subset are true landmarks. Constraining the horizontal disparity limits the amount of spurious matches. The stereo matching is validated by finding which landmarks survives short motions measured with a complementary navigation system, like odometry, thus transferring the stereo matching problem from two to three dimensional space and robot motion is estimated from the landmarks surviving the motion. The results from our experiments show that the spurious matching algorithm for stereo matching validation works and that the system is able to estimate the motion.
Emerging Technologies & Factory Automation, 2009. ETFA 2009. IEEE Conference on; 10/2009
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ABSTRACT: Current approaches to feature detection and matching in images strive to increase the repeatability of the detector and minimize the degree of outliers in the matching. In this paper we present a new approach; we suggest that a lower performance feature detector can produce a result more than adequate for robot navigation irrespectively of the amount of outliers. By using an FPGA together with two cameras we can remove the need for descriptors by performing what we call spurious matching and the use of 3D landmarks. The approach bypasses the problem of outliers and reduces the time consuming task of data association, which slows many matching algorithms down.
Emerging Technologies and Factory Automation, 2008. ETFA 2008. IEEE International Conference on; 10/2008
