35,113 research outputs found

    Data-Driven Grasp Synthesis - A Survey

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    We review the work on data-driven grasp synthesis and the methodologies for sampling and ranking candidate grasps. We divide the approaches into three groups based on whether they synthesize grasps for known, familiar or unknown objects. This structure allows us to identify common object representations and perceptual processes that facilitate the employed data-driven grasp synthesis technique. In the case of known objects, we concentrate on the approaches that are based on object recognition and pose estimation. In the case of familiar objects, the techniques use some form of a similarity matching to a set of previously encountered objects. Finally for the approaches dealing with unknown objects, the core part is the extraction of specific features that are indicative of good grasps. Our survey provides an overview of the different methodologies and discusses open problems in the area of robot grasping. We also draw a parallel to the classical approaches that rely on analytic formulations.Comment: 20 pages, 30 Figures, submitted to IEEE Transactions on Robotic

    Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks

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    A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One way of such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable to establish a common focus of attention and be able to use and integrate spoken instructions, visual perceptions, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and an modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.Comment: 7 pages, 8 figure

    Natural Virtual Reality User Interface to Define Assembly Sequences for Digital Human Models

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    Digital human models (DHMs) are virtual representations of human beings. They are used to conduct, among other things, ergonomic assessments in factory layout planning. DHM software tools are challenging in their use and thus require a high amount of training for engineers. In this paper, we present a virtual reality (VR) application that enables engineers to work with DHMs easily. Since VR systems with head-mounted displays (HMDs) are less expensive than CAVE systems, HMDs can be integrated more extensively into the product development process. Our application provides a reality-based interface and allows users to conduct an assembly task in VR and thus to manipulate the virtual scene with their real hands. These manipulations are used as input for the DHM to simulate, on that basis, human ergonomics. Therefore, we introduce a software and hardware architecture, the VATS (virtual action tracking system). This paper furthermore presents the results of a user study in which the VATS was compared to the existing WIMP (Windows, Icons, Menus and Pointer) interface. The results show that the VATS system enables users to conduct tasks in a significantly faster way

    Online weight estimation in a robotic gripper arm

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    This paper presents a novel methodology for online, fast and accurate weight estimation technique in a robotic gripper arm. The laboratory setup is inspired from several real life applications of weight estimation in moving cranes, e.g. loading containers in a shipyard, iron scrapping in steel industry, etc. The weight needs to be estimated within a specified time interval and within a tolerance interval for accuracy. The results indicate that the proposed method is suitable for this kind of application and an improvement of 30% has been achieved compared to the current state of work
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