An Autonomous Mapping Method for Robot Based on Efficient Frontier Exploration

Liu Rui-xue; Zeng Bi; Wang Ming-hui; Lu Zhi-liang

doi:10.12052/gdutxb.200030

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An Autonomous Mapping Method for Robot Based on Efficient Frontier Exploration

更新时间：2026-05-27

- An Autonomous Mapping Method for Robot Based on Efficient Frontier Exploration
- Vol. 37, Issue 5, Pages: 38-45(2020)
- 作者机构：
  
  广东工业大学计算机学院,广东,广州,510006
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.200030
  CLC： TP399
- Online First：17 September 2020，
  
  Published：2020
- 稿件说明：
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刘瑞雪, 曾碧, 汪明慧, 卢智亮. 一种基于高效边界探索的机器人自主建图方法[J]. 广东工业大学学报, 2020, 37(5): 38-45.

Liu Rui-xue, Zeng Bi, Wang Ming-hui, et al. An Autonomous Mapping Method for Robot Based on Efficient Frontier Exploration[J]. 2020, 37(5): 38-45.
刘瑞雪, 曾碧, 汪明慧, 卢智亮. 一种基于高效边界探索的机器人自主建图方法[J]. 广东工业大学学报, 2020, 37(5): 38-45. DOI： 10.12052/gdutxb.200030.

Liu Rui-xue, Zeng Bi, Wang Ming-hui, et al. An Autonomous Mapping Method for Robot Based on Efficient Frontier Exploration[J]. 2020, 37(5): 38-45. DOI： 10.12052/gdutxb.200030.

摘要

针对目前自主移动机器人对室内未知环境的自主探索建图效率低、通用性差以及由于探索区域狭窄导致地图构建不完整的问题

提出一种基于曲线拟合和目标探索点邻域规划的边界探索自主建图方法。该方法对已构建的初始地图边界以曲线拟合方式筛选安全目标探索区

并针对机器人不可达目标探索区

采取滑动窗口邻域规划方法建立新目标探索点

引导机器人自主导航至该目标探索点

同时利用同步定位与建图技术

完成机器人对未知环境的自主探索和构图。实验表明

与现有方法比较

本方法能够以较少的探索次数、更短的探索路径和更高的探索效率完成对未知室内复杂场景的自主探索建图。

Abstract

An improved autonomous frontier exploration method is presented to solve the problems of autonomous mobile robot autonomously exploring indoor unknown environments with low efficiency

poor versatility

and incomplete map construction due to the narrow exploration area. The curve fitting method is used to screen the safety target exploration area for the constructed initial map frontier and for the robot unreachable target exploration area

adopting a sliding window neighborhood planning method to establish a new target exploration point

guiding the robot to autonomously navigate to the target exploration point

while using simultaneous localization and mapping technology to complete the robot's autonomous exploration and mapping of unknown environments. The experimental results show that the method can better solve the problems of narrow target area and unreachable target points in the traditional algorithm. And it can complete autonomous exploration and mapping of unknown indoor complex scenes with fewer exploration times

shorter exploration paths and higher exploration efficiency.

关键词

Keywords

references

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