量子算法辅助机器人定位

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems Pub Date : 2025-04-26 DOI:10.1016/j.robot.2025.105026

Unai Antero , Basilio Sierra , Jon Oñativia , Alejandra Ruiz , Eneko Osaba

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引用次数: 0

摘要

定位是移动机器人的一个关键方面，它使机器人能够有效地导航其环境并避开障碍物。目前的概率定位方法，如自适应蒙特卡罗定位（AMCL）算法，计算量大，可能难以处理大地图或高分辨率传感器数据。本文探讨了量子计算在机器人技术中的应用，重点研究了利用Grover搜索算法来提高移动机器人的定位效率。我们提出了一种新的方法来利用格罗弗算法在二维地图，实现更快和更有效的定位。尽管目前的物理量子计算机存在局限性，但我们的实验结果表明，与经典方法相比，量子计算的速度有了显著提高，突出了量子计算改善机器人定位的潜力。这项工作弥合了量子计算和机器人之间的差距，为机器人定位提供了一个实用的解决方案，并为未来量子机器人的研究铺平了道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Robot localization aided by quantum algorithms

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Robot localization aided by quantum algorithms

Localization is a critical aspect of mobile robotics, enabling robots to navigate their environment efficiently and avoid obstacles.

Current probabilistic localization methods, such as the Adaptive Monte Carlo localization (AMCL) algorithm, are computationally intensive and may struggle with large maps or high resolution sensor data.

This paper explores the application of quantum computing in robotics, focusing on the use of Grover’s search algorithm to improve the efficiency of localization in mobile robots. We propose a novel approach to utilize Grover’s algorithm in a 2D map, enabling faster and more efficient localization.

Despite the limitations of current physical quantum computers, our experimental results demonstrate a significant speedup over classical methods, highlighting the potential of quantum computing to improve robotic localization. This work bridges the gap between quantum computing and robotics, providing a practical solution for robotic localization and paving the way for future research in quantum robotics.

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来源期刊

Robotics and Autonomous Systems 工程技术-机器人学

CiteScore

9.00

自引率

7.00%

发文量

164

审稿时长

4.5 months

期刊介绍： Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.