测绘学报 ›› 2021, Vol. 50 ›› Issue (11): 1457-1468.doi: 10.11947/j.AGCS.2021.20210290

• 智能驾驶环境感知 • 上一篇    下一篇

深空探测车环境感知与导航定位技术进展与展望

邸凯昌1, 王镓2, 邢琰3, 刘召芹1, 万文辉1, 彭嫚1, 王晔昕1, 刘斌1, 于天一2, 李立春2, 刘传凯2   

  1. 1. 中国科学院空天信息创新研究院遥感科学国家重点实验室, 北京 100101;
    2. 北京航天飞行控制中心, 北京 100094;
    3. 北京控制工程研究所, 北京 100094
  • 收稿日期:2021-05-20 修回日期:2021-07-15 发布日期:2021-12-07
  • 通讯作者: 万文辉 E-mail:wanwh@radi.ac.cn
  • 作者简介:邸凯昌(1967—),男,研究员,研究方向为行星遥感制图与导航定位。
  • 基金资助:
    国家重点研发计划(2018YFB1305004)

Progresses and prospects of environment perception and navigation for deep space exploration rovers

DI Kaichang1, WANG Jia2, XING Yan3, LIU Zhaoqin1, WAN Wenhui1, PENG Man1, WANG Yexin1, LIU Bin1, YU Tianyi2, LI Lichun2, LIU Chuankai2   

  1. 1. State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China;
    2. Beijing Aerospace Control Center (BACC), Beijing 100094, China;
    3. Beijing Institute of Control Engineering, Beijing 100194, China
  • Received:2021-05-20 Revised:2021-07-15 Published:2021-12-07
  • Supported by:
    The National Key Research and Development Program of China (No. 2018YFB1305004)

摘要: 环境感知与导航定位是深空探测车自动驾驶的核心技术,由于深空环境的特殊性,深空探测车的环境感知与导航定位与地球上汽车自动驾驶的相应技术相比面临独特的挑战。本文从实际工程应用和科研进展两个角度总结了深空探测车环境感知、视觉定位、路径规划等关键技术的进展,并对未来深空探测车智能感知与长距离导航定位等发展方向进行了探讨与展望。

关键词: 深空探测, 月球车, 火星车, 环境感知, 视觉定位, 路径规划

Abstract: Environment perception and navigation are the core technologies for automated driving of deep space exploration rovers. Due to the special circumstances of the deep space environment, the rover’s environment perception and navigation are particularly challenging comparing to the corresponding technologies in autonomous car driving on Earth. The paper presents a review of the progresses of environment perception, rover localization and path planning, from engineering application and scientific research perspectives. Moreover, the future prospects of intelligent environment perception and long-range rover navigation are discussed.

Key words: deep space exploration, lunar rover, Mars rover, environment perception, visual localization, path planning

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