活跃的SLAM:对过去十年的回顾
Muhammad Farhan Ahmed1, Khayyam Masood2, Vincent Fremont1
1Laboratoire des Sciences du Numérique de Nantes (LS2N), CNRS, Ecole Centrale de Nantes, 1 Rue de la Noë, 44300 Nantes, France.
Sensors (Basel, Switzerland)
|October 14, 2023
概括
本综述调查了过去十年的Active Simultaneous Localization and Mapping (A-SLAM),涵盖了它的制定,应用和方法. 它还介绍了积极协作SLAM (AC-SLAM) 分析,确定了研究缺口和未来方向.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 人工智能的人工智能
- 计算机视觉 计算机视觉
背景情况:
- 同时定位和映射 (SLAM) 对自主系统至关重要.
- 主动SLAM (A-SLAM) 通过优化机器人运动和传感器动作来提高效率.
- 现有的研究已经探索了各种A-SLAM配方和应用.
研究的目的:
- 为过去十年的A-SLAM研究提供全面的回顾.
- 介绍一个新的分析活动协作SLAM (AC-SLAM).
- 确定A-SLAM的局限性,并建议未来的研究方向.
主要方法:
- 综述A-SLAM文献,重点关注轨迹生成和控制-动作选择.
- 信息理论 (IT) 和最佳实验设计理论 (TOED) 的应用.
- 对A-SLAM方法,场景和实用功能的定性和定量分析.
- 考察AC-SLAM中的协作参数和方法.
主要成果:
- 详细概述A-SLAM方法,包括路径规划和公用事业功能.
- 对AC-SLAM进行了新的分析,评估了协作方面的方面.
- 在当前的A-SLAM文献中发现研究缺口和局限性.
结论:
- A-SLAM研究已经取得了显著的进步,采用了各种方法和应用.
- AC-SLAM为未来的协作机器人研究提供了一个有前途的领域.
- 这项调查对A-SLAM领域的研究人员来说是一个宝贵的资源.
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