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Reducing uncertainty in robotic surface assembly tasks based on contact information

机译:根据联系信息减少机器人表面组装任务中的不确定性

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In contrast to hard automation, flexible assembly using a general-purpose robot holds the promise of reducing costs and increasing productivity of small batch products as well as adaptivity to product changes. However, robotic assembly remains one of the most challenging problems in robotics research. In particular, it has to overcome uncertainty in the environment and the location of parts. This paper addresses how to estimate and correct part positioning uncertainties with respect to the assembly task by using the contact trajectory data collected during active part interaction. We first devise a nominal assembly motion sequence based on an approximate knowledge of the poses of the parts, which includes exploratory compliant moves for the purpose of parameter estimation. As the robot manipulator executes the nominal motion sequence, data collected during exploratory compliant moves are used to estimate part poses more accurately, and the improved information is used to update the subsequent assembly motion sequence to correct errors in the nominal plan. We implemented the strategy using a back-drivable Barrett WAM robotic arm without a force sensor and BarrettHand BH8-262. The empirical results have demonstrated the effectiveness of our approach.
机译:与硬自动化相比,使用通用机器人的灵活组装有望降低成本,提高小批量产品的生产率以及对产品变更的适应性。然而,机器人组装仍然是机器人研究中最具挑战性的问题之一。特别是,它必须克服环境和零件位置的不确定性。本文介绍了如何通过使用在活动零件交互过程中收集的接触轨迹数据来估计和校正相对于装配任务的零件定位不确定性。我们首先根据零件姿势的近似知识设计名义上的装配运动序列,其中包括出于参数估计目的的探索性顺应运动。随着机器人操纵器执行名义运动序列,在探索性顺应性移动过程中收集的数据将用于更准确地估计零件姿态,而改进的信息将用于更新后续的装配运动序列,以更正名义计划中的错误。我们使用可向后驱动的Barrett WAM机械臂(没有力传感器)和BarrettHand BH8-262来实施该策略。实证结果证明了我们方法的有效性。

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