基于拓扑和微分几何的机器人路径规划最新综述--第二部分:动态约束条件下的规划

IF 2.1 Q3 ROBOTICS
Sindhu Radhakrishnan, Wail Gueaieb
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引用次数: 0

摘要

无论是工业机器人、研究机器人还是消费机器人,路径规划都是自主机器人技术的内在组成部分。这些途径都会遇到必须规划路径的限制因素。虽然选择合适的算法与应用有关,但理想路径规划算法的出发点是回顾过去的工作。从历史上看,算法的分类基于自主机器人技术的三个原则,即避开不同约束的能力(静态/动态)、环境知识(已知/未知)和机器人知识(一般/特定模型)。然而,文献中的这种划分并不全面,尤其是在动态约束方面。因此,为了解决这一问题,我们提出了一种新的分类法,其基本原则是描述空间的特征,即空间是一组不同的、不相关的点,或者是一组具有共同关系的点。我们的研究表明,这种分类法能有效解决路径规划的重要参数问题,如空间的连通性和分割。因此,路径规划空间现在既可以被视为点的集合,也可以被视为具有结构的空间。前者在很大程度上依赖于机器人模型,因为没有考虑环境的数学结构。因此,所采用的方法是优化算法的变体和基于模型方法的特定变体,这些方法都是为消除动态约束的影响而量身定制的。后者将空间描述为具有相互连接关系的点,如曲面或流形。这些结构允许使用基于同构的方法对路径进行独特的描述。因此,从动态约束的角度来看,这项工作的目标如下:首先,我们为机器人路径规划文献提出了一个包罗万象的分类法,该分类法考虑了空间的基本结构。其次,我们对那些专注于描述空间中路径特征的著作进行了详细的积累,这些著作都是为了显示潜在结构而制定的。这项工作通过以下方式实现目标:它强调了路径规划文献的现有分类,找出了常见分类中的不足,提出了基于路径规划空间数学性质(拓扑特性)的新分类法,并提供了该新分类法所涵盖的大量文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A state-of-the-art review on topology and differential geometry-based robotic path planning—part II: planning under dynamic constraints

A state-of-the-art review on topology and differential geometry-based robotic path planning—part II: planning under dynamic constraints

Path planning is an intrinsic component of autonomous robotics, be it industrial, research or consumer robotics. Such avenues experience constraints around which paths must be planned. While the choice of an appropriate algorithm is application-dependent, the starting point of an ideal path planning algorithm is the review of past work. Historically, algorithms were classified based on the three tenets of autonomous robotics which are the ability to avoid different constraints (static/dynamic), knowledge of the environment (known/unknown) and knowledge of the robot (general/model specific). This division in literature however, is not comprehensive, especially with respect to dynamics constraints. Therefore, to remedy this issue, we propose a new taxonomy, based on the fundamental tenet of characterizing space, i.e., as a set of distinct, unrelated points or as a set of points that share a relationship. We show that this taxonomy is effective in addressing important parameters of path planning such as connectivity and partitioning of spaces. Therefore, path planning spaces may now be viewed either as a set of points or, as a space with structure. The former relies heavily on robot models, since the mathematical structure of the environment is not considered. Thus, the approaches used are variants of optimization algorithms and specific variants of model-based methods that are tailored to counteract effects of dynamic constraints. The latter depicts spaces as points with inter-connecting relationships, such as surfaces or manifolds. These structures allow for unique characterizations of paths using homotopy-based methods. The goals of this work, viewed specifically in light with dynamic constraints, are therefore as follows: First, we propose an all-encompassing taxonomy for robotic path planning literature that considers an underlying structure of the space. Second, we provide a detailed accumulation of works that do focus on the characterization of paths in spaces formulated to show underlying structure. This work accomplishes the goals by doing the following: It highlights existing classifications of path planning literature, identifies gaps in common classifications, proposes a new taxonomy based on the mathematical nature of the path planning space (topological properties), and provides an extensive conglomeration of literature that is encompassed by this new proposed taxonomy.

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来源期刊
CiteScore
3.80
自引率
5.90%
发文量
50
期刊介绍: The International Journal of Intelligent Robotics and Applications (IJIRA) fosters the dissemination of new discoveries and novel technologies that advance developments in robotics and their broad applications. This journal provides a publication and communication platform for all robotics topics, from the theoretical fundamentals and technological advances to various applications including manufacturing, space vehicles, biomedical systems and automobiles, data-storage devices, healthcare systems, home appliances, and intelligent highways. IJIRA welcomes contributions from researchers, professionals and industrial practitioners. It publishes original, high-quality and previously unpublished research papers, brief reports, and critical reviews. Specific areas of interest include, but are not limited to:Advanced actuators and sensorsCollective and social robots Computing, communication and controlDesign, modeling and prototypingHuman and robot interactionMachine learning and intelligenceMobile robots and intelligent autonomous systemsMulti-sensor fusion and perceptionPlanning, navigation and localizationRobot intelligence, learning and linguisticsRobotic vision, recognition and reconstructionBio-mechatronics and roboticsCloud and Swarm roboticsCognitive and neuro roboticsExploration and security roboticsHealthcare, medical and assistive roboticsRobotics for intelligent manufacturingService, social and entertainment roboticsSpace and underwater robotsNovel and emerging applications
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