[1]高宇,霍静,李文斌,等.基于路径规划特点的语义目标导航方法[J].智能系统学报,2024,19(1):217-227.[doi:10.11992/tis.202309001]
　GAO Yu,HUO Jing,LI Wenbin,et al.Object goal navigation based on path planning characteristics[J].CAAI Transactions on Intelligent Systems,2024,19(1):217-227.[doi:10.11992/tis.202309001]
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基于路径规划特点的语义目标导航方法

《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷: 19 期数: 2024年第1期 页码: 217-227 栏目: 人工智能院长论坛 出版日期: 2024-01-05
Title:
Object goal navigation based on path planning characteristics
作者:
高宇1, 霍静1, 李文斌1, 伍静2, 来煜坤2, 高阳1
1. 南京大学 计算机软件新技术全国重点实验室, 江苏 南京 210023;
2. 卡迪夫大学 计算机科学与信息学院, 英国 威尔士卡迪夫 CF10 3XQ
Author(s):
GAO Yu1, HUO Jing1, LI Wenbin1, WU Jing2, LAI Yukun2, GAO Yang1
1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China;
2. School of Computer Science and Informatics, Cardiff University, Cardiff CF10 3XQ , England
关键词:
人工智能; 视觉导航; 语义目标导航; 语义感知; 语义探索; 路径规划; 机器学习; 语义地图
Keywords:
artificial intelligence; visual navigation; object goal navigation; semantic perception; semantic exploration; path planning; machine learning; semantic map
分类号:
TP399
DOI:
10.11992/tis.202309001
文献标志码:
2024-01-03
摘要:
为了解决语义目标导航任务中存在的探索效率低、深度不精准等问题，本文构建了一个解决语义目标导航任务的框架，在语义地图构建模块中引入了深度图边缘处理以及地图纠错机制；在探索模块中引入了覆盖范围最大化算法；在路径规划模块中引入了替代点机制。本文在一个3D仿真环境下进行了实验。实验结果表明，本文提出的解决方案明显提升了语义目标导航任务的性能。此外，本文所提方法成功应用到了四足机器人上，从而验证了其在现实场景下的泛化性。
Abstract:
To solve the problems of low exploration efficiency and imprecise depth in object goal navigation, this article constructs a framework to solve object goal navigation. Depth map edge processing and map error correction mechanisms were introduced in the semantic map construction module; a coverage maximization algorithm was introduced in the exploration module; alternative point mechanisms was introduced in the path planning module. This article conducted experiments in a 3D simulation environment. The experimental results show that the new solution proposed in this article significantly improves the performance of object goal navigation. In addition, the method proposed in this article was successfully applied to quadruped robots, thereby verifying its generalization in real-world scenarios.
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备注/Memo

收稿日期:2023-09-01。
基金项目:科技部2030新一代人工智能项目（2021ZD0113303）；国家自然科学基金项目（62276128，62192783，62106100）；江苏省重点研发项目（BE2022077）
作者简介:高宇，硕士研究生，主要研究方向为机器人导航、具身智能。E-mail：gaoyu@smail.nju.edu.cn;霍静，准聘副教授，博士， 中国计算机学会人工智能与模式识别专委会委员、中国人工智能学会粒计算与知识发现专委委员，主要研究方向为机器学习、计算机视觉和具身智能。主持国家自然科学基金面上和青年项目各1项，获 2018 年江苏省科学技术奖二等奖。发表学术论文40余篇。E-mail：huojing@nju.edu.cn;李文斌，副研究员，博士， 中国人工智能学会机器学习专委会委员、中国人工智能学会智能服务专委会委员、江苏省人工智能学会机器学习专委会秘书长，主要研究方向为机器学习、计算机视觉和软硬件协同。获2023年中国科协人才托举项目，主持国家自然科学基金青年基金项目1项、江苏省自然科学基金面上项目1项，参与国家自然科学基金重大项目1项。发表学术论文30余篇。E-mail：liwenbin@nju.edu.cn
通讯作者:霍静. E-mail：huojing@nju.edu.cn

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