A new interaction force decomposition maximizing compensating forces under physical work constraints

Alexander M. Schmidts, Manuel Schneider, Markus Kuhne, A. Peer
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引用次数: 2

Abstract

In manipulation tasks interaction forces are often decomposed to be able to control robustness-reflective and accelerating forces separately. While this decomposition is typically performed for the synthesis of interaction forces to be applied for example in the context of robotic grasping, less attention has been paid to the analysis of measured, human interaction forces. Here, we introduce a physically-motivated bounding constraint, based on the law of energy conservation, and present a new decomposition approach for interaction force analysis with rigid objects. The decomposition extends the intuitive solution known in literature for the two finger grasp by maximizing robustness-reflective forces while respecting the bounding constraint. Advantages of our approach are illustrated in numerical examples and experiments and by comparing it to existing decomposition approaches. In contrast to existing approaches, our new approach is not limited in the number of interaction points and incorporates only individual interaction forces which are physically plausible.
一种新的在物理功约束下补偿力最大化的相互作用力分解方法
在操作任务中,通常将交互力分解为能够分别控制鲁棒性反射力和加速力。虽然这种分解通常是为了综合应用的相互作用力而进行的,例如在机器人抓取的背景下,对测量的人类相互作用力的分析关注较少。在此,我们引入了基于能量守恒定律的物理驱动边界约束,并提出了一种新的分解方法来分析刚体相互作用力。该分解扩展了文献中已知的两指抓取的直观解,通过最大化鲁棒性反射力,同时尊重边界约束。通过数值算例和实验,并与现有的分解方法进行了比较,说明了本文方法的优点。与现有方法相比,我们的新方法不受相互作用点数量的限制,并且只包含物理上合理的单个相互作用力。
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