6,879 research outputs found

    Object and Relation Centric Representations for Push Effect Prediction

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    Pushing is an essential non-prehensile manipulation skill used for tasks ranging from pre-grasp manipulation to scene rearrangement, reasoning about object relations in the scene, and thus pushing actions have been widely studied in robotics. The effective use of pushing actions often requires an understanding of the dynamics of the manipulated objects and adaptation to the discrepancies between prediction and reality. For this reason, effect prediction and parameter estimation with pushing actions have been heavily investigated in the literature. However, current approaches are limited because they either model systems with a fixed number of objects or use image-based representations whose outputs are not very interpretable and quickly accumulate errors. In this paper, we propose a graph neural network based framework for effect prediction and parameter estimation of pushing actions by modeling object relations based on contacts or articulations. Our framework is validated both in real and simulated environments containing different shaped multi-part objects connected via different types of joints and objects with different masses. Our approach enables the robot to predict and adapt the effect of a pushing action as it observes the scene. Further, we demonstrate 6D effect prediction in the lever-up action in the context of robot-based hard-disk disassembly.Comment: Project Page: https://fzaero.github.io/push_learning

    Real Time Animation of Virtual Humans: A Trade-off Between Naturalness and Control

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    Virtual humans are employed in many interactive applications using 3D virtual environments, including (serious) games. The motion of such virtual humans should look realistic (or ‘natural’) and allow interaction with the surroundings and other (virtual) humans. Current animation techniques differ in the trade-off they offer between motion naturalness and the control that can be exerted over the motion. We show mechanisms to parametrize, combine (on different body parts) and concatenate motions generated by different animation techniques. We discuss several aspects of motion naturalness and show how it can be evaluated. We conclude by showing the promise of combinations of different animation paradigms to enhance both naturalness and control

    VizLab: The Design and Implementation of An Immersive Virtual Environment System Using Game Engine Technology and Open Source Software

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    Virtual Reality (VR) is a term used to describe computer-simulated environments that can immerse users in a real or unreal world. Immersive systems are an essential component when experiencing virtual environments. Developing VR applications is time-consuming, and developers use many resources in creating VR applications. The separate components require integration, and the challenges in using public domain open source software present complex software development. The VizLab Virtual Reality System was created to meet these challenges and provide an integrated suite of tools for VR system development. VizLab supports the development of VR applications by using game engine and CAVE system technology. The system consists of software modules that provide rendering, texturing, collision, physics, window/viewport management, cluster synchronization, input management, multi-processing, stereoscopic 3D, and networking. VizLab combines the main functional aspects of a game engine and CAVE system for an improved approach to developing VR applications, virtual environments, and immersive environments
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