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Dextrous Manipulation from a Grasping Pose

机译:抓握姿势的灵巧操作

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This paper introduces an optimization-based approach to synthesizing hand manipulations from a starting grasping pose. We describe an automatic method that takes as input an initial grasping pose and partial object trajectory, and produces as output physically plausible hand animation that effects the desired manipulation. In response to different dynamic situations during manipulation, our algorithm can generate a range of possible hand manipulations including changes in joint configurations, changes in contact points, and changes in the grasping force. Formulating hand manipulation as an optimization problem is key to our algorithm's ability to generate a large repertoire of hand motions from limited user input. We introduce an objective function that accentuates the detailed hand motion and contacts adjustment. Furthermore, we describe an optimization method that solves for hand motion and contacts efficiently while taking into account long-term planning of contact forces. Our algorithm does not require any tuning of parameters, nor does it require any prescribed hand motion sequences.
机译:本文介绍了一种基于优化的方法,可以从抓握姿势开始综合手部操作。我们描述了一种自动方法,该方法采用初始抓握姿势和部分物体轨迹作为输入,并产生可实现所需操纵的物理上合理的手动画作为输出。响应于操作过程中的不同动态情况,我们的算法可以生成一系列可能的手操作,包括关节构型的变化,接触点的变化以及抓握力的变化。将手操作描述为优化问题是我们算法从有限的用户输入中生成大量手部动作的能力的关键。我们引入了一个目标功能,以强调详细的手部运动和接触调整。此外,我们描述了一种优化方法,该方法可以有效解决手部运动和接触问题,同时考虑到接触力的长期规划。我们的算法不需要任何参数调整,也不需要任何规定的手部动作序列。

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