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A 3D grasping system based on multimodal visual and tactile processing

机译:一种基于多模态视觉和触觉处理的三维抓取系统

摘要

urpose – The purpose of this paper is to present a novel multimodal approach to the problem of planning and performing a reliable grasping action on unmodeled objects. Design/methodology/approach – The robotic system is composed of three main components. The first is a conceptual manipulation framework based on grasping primitives. The second component is a visual processing module that uses stereo images and biologically inspired algorithms to accurately estimate pose, size, and shape of an unmodeled target object. A grasp action is planned and executed by the third component of the system, a reactive controller that uses tactile feedback to compensate possible inaccuracies and thus complete the grasp even in difficult or unexpected conditions.Findings – Theoretical analysis and experimental results have shown that the proposed approach to grasping based on the concurrent use of complementary sensory modalities, is very promising and suitable even for changing, dynamic environments. Research limitations/implications – Additional setups with more complicate shapes are being investigated, and each module is being improved both in hardware and software.Originality/value – This paper introduces a novel, robust, and flexible grasping system based on multimodal integration.
机译:目的–本文的目的是提出一种新颖的多峰方法,以解决对未建模对象进行计划和执行可靠抓取动作的问题。设计/方法/方法–机器人系统由三个主要组件组成。第一个是基于掌握原语的概念操纵框架。第二个组件是视觉处理模块,该模块使用立体图像和生物学启发的算法来准确估算未建模目标对象的姿态,大小和形状。抓取动作是由系统的第三部分计划和执行的,该系统是一种无功控制器,它使用触觉反馈来补偿可能的不准确性,从而即使在困难或意外的情况下也可以完成抓取。发现–理论分析和实验结果表明,提出的方案基于同时使用互补感觉模态的抓握方法非常有前途,甚至适用于变化多端的动态环境。研究的局限性/意义–正在研究具有更复杂形状的其他设置,并且还在硬件和软件方面对每个模块进行改进。原创性/价值–本文介绍了一种基于多模式集成的新颖,强大且灵活的抓取系统。

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