中国空间科学技术

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地外探测基于多光谱特性的土壤力学特性反演试验研究

张洪嘉1,邢琰1,2,*,杨伟奇1   

  1. 1.北京控制工程研究所,北京100094
    2.空间智能控制技术全国重点实验室,北京100094
  • 收稿日期:2025-07-08 修回日期:2025-08-07 录用日期:2025-08-15 发布日期:2026-01-13 出版日期:2026-01-13

Experimental study on soil mechanics property inference for extraterrestrial exploration based on multispectral characteristics

ZHANG Hongjia1,XING Yan1,2,*,YANG Weiqi1   

  1. 1.Beijing Institute of Control Engineering,Beijing 100094,China
    2.National Key Laboratory of Space Intelligent Control,Beijing 100094,China
  • Received:2025-07-08 Revision received:2025-08-07 Accepted:2025-08-15 Online:2026-01-13 Published:2026-01-13

摘要: 地外探测移动机器人巡视探测是拓展深空探测广度和深度的有效方式。然而当前在轨移动机器人采用的传统感知方法,在地外环境形貌原始自然、纹理相似度高、光照差异大,且缺少先验知识的条件下,难以有效识别非几何障碍(如松软沙区),进而影响移动机器人的安全运行。研究设计了基于多光谱特性的土壤力学特性反演试验研究:通过贝氏仪原位测量试验与光谱特性测量试验,构建涵盖多种模拟土壤的光谱特性曲线及对应的力学特性参数数据库;建立“光谱特性-土壤类型-力学特性”的分级映射机制,定性推断土壤力学特性;采用祝融号在轨多光谱图像数据进行测试验证。验证结果表明,通过分析巡视区域光谱特性识别主导土壤类型,并根据数据库关联其典型力学特性参数,可定性推断土壤力学特性,为地外机器人安全路径规划提供决策支持。

关键词: 地外探测, 移动机器人, 多光谱, 力学特性

Abstract: Roving exploration using mobile robots is crucial for extending the breadth and depth of deep space exploration. However, current terrestrial perception methods employed by mobile robots in orbit struggle to effectively identify non-geometric hazards(such as soft sandy areas) under extraterrestrial conditions characterized by rugged and natural terrain, high texture homogeneity, extreme illumination variations, and limited prior knowledge. This limitation consequently compromises the navigational safety of mobile robots.This study designs a soil mechanical properties inference experiment based on multispectral characteristics: spectral characteristics curves and corresponding mechanical parameter databases covering multiple simulated soils are constructed through spectral characteristic measurement experiments and in-situ Bevameter mechanical properties measurement experiments; a hierarchical mapping mechanism of "spectral characteristics-soil type-mechanical properties" is established to qualitatively infer soil mechanical properties; validation is conducted using multispectral image data captured by Zhurong rover. The validation results demonstrate that identifying dominant soil types through spectral features and correlating them with mechanical properties via database allows qualitative inference of surface mechanical parameters, which provides decision support for safe path planning of extraterrestrial robots.

Key words: extraterrestrial exploration, mobile robot, multi spectrum, mechanical properties