论文标题

通用的非线性和鳍的几何形状用于机器人技术

Generalized Nonlinear and Finsler Geometry for Robotics

论文作者

Ratliff, Nathan D., Van Wyk, Karl, Xie, Mandy, Li, Anqi, Rana, Muhammad Asif

论文摘要

Robotics Research发现了Riemannian几何形状的许多重要应用。尽管如此,对于许多机器人主义者来说,这个概念仍然具​​有挑战性,因为背景材料很复杂且惊人的外国。除了{\ em riemannian}几何形状之外,数学文献中还有许多自然概括 - 诸如Finsler几何形状和喷雾几何形状等区域 - 但这些概括在很大程度上是无法访问的,因此,机器人技术中几乎没有应用。本文提出了对喷雾和鳍的几何形状的重新衍生,我们发现对我们最近在强大的行为设计工具上开发我们称为几何织物的工作至关重要。这些派生从高级演算中的基本工具和变化的计算中构建,使机器人受众比标准演示更容易访问它们。我们专注于务实和可计算的结果,避免使用张量表示法吸引更广泛的受众,从而强调了几何路径一致性对围绕连接和曲率的思想的一致性。我们希望这些派生将有助于对通用非线性,甚至是经典的Riemannian,机器人社区中的几何形状的了解,并激发未来对新应用的研究。

Robotics research has found numerous important applications of Riemannian geometry. Despite that, the concept remain challenging to many roboticists because the background material is complex and strikingly foreign. Beyond {\em Riemannian} geometry, there are many natural generalizations in the mathematical literature -- areas such as Finsler geometry and spray geometry -- but those generalizations are largely inaccessible, and as a result there remain few applications within robotics. This paper presents a re-derivation of spray and Finsler geometries we found critical for the development of our recent work on a powerful behavioral design tool we call geometric fabrics. These derivations build from basic tools in advanced calculus and the calculus of variations making them more accessible to a robotics audience than standard presentations. We focus on the pragmatic and calculable results, avoiding the use of tensor notation to appeal to a broader audience, emphasizing geometric path consistency over ideas around connections and curvature. We hope that these derivations will contribute to an increased understanding of generalized nonlinear, and even classical Riemannian, geometry within the robotics community and inspire future research into new applications.

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