2022
DOI: 10.1109/access.2022.3196340
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Predicting Rigid Body Dynamics Using Dual Quaternion Recurrent Neural Networks With Quaternion Attention

Abstract: We propose a novel neural network architecture based on dual quaternions which allow for a compact representation of information with a main focus on describing rigid body movements. After introducing the underlying dual quaternion math, we derive dual quaternion valued neural network layer which are generally applickable to all sorts of problems which can benefit from a mathematical description in dual quaternion space. To cover the dynamic behavior inherent to rigid body movements, we propose recurrent archi… Show more

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Cited by 7 publications
(3 citation statements)
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“…Thanks to such representation, we can enclose a full rigid motion, i.e., translation and rotation, in a single entity [19], considering object movements in the space as a combination of highly-correlated elements. Differently from previous attempts that only focus on simulated tests [20,21], we model human skeleton motions in real-world scenarios, showing the crucial role of the dual quaternion representation in learning body translations in space. Moreover, we provide practical proof that our dual quaternion formulation is both translation and rotation equivariant, which are highly desirable properties for all applications involving 3D movement modeling.…”
Section: Introductionmentioning
confidence: 93%
“…Thanks to such representation, we can enclose a full rigid motion, i.e., translation and rotation, in a single entity [19], considering object movements in the space as a combination of highly-correlated elements. Differently from previous attempts that only focus on simulated tests [20,21], we model human skeleton motions in real-world scenarios, showing the crucial role of the dual quaternion representation in learning body translations in space. Moreover, we provide practical proof that our dual quaternion formulation is both translation and rotation equivariant, which are highly desirable properties for all applications involving 3D movement modeling.…”
Section: Introductionmentioning
confidence: 93%
“…Moreover, control laws based on the dual quaternion involving combined position and attitude intrinsically account for the natural coupling between the rotational and translational motion [1]. The widespread use of dual quaternions can be found in robotics systems [2] [3], rigid body dynamics [4] [5] [6], and in relative spacecraft system dynamics [7] [8]. They are also utilized in field of aerospace engineering involving dual quaternions for powered descent [9] and satellite autonomous rendezvous control [10] [11].…”
Section: Introductionmentioning
confidence: 99%
“…n-dimensional data without modifications to architectural layers. For that reason, the already ample field of hypercomplex models based on complex [1], quaternion [2], dual quaternion [3,4], and octonion [1] numbers has been permeated by PHNNs. These networks have been defined with different known backbones such as ResNets [5,6], GANs [7,8], graph neural networks [9], and Transformers [10], among others [11,12].…”
Section: Introductionmentioning
confidence: 99%