Lunar helium-3 is a highly valuable strategic resource, pivotal to the advancement of both deep-space exploration and space mining. Existing lunar helium-3 exploration methodologies rely primarily on indirect measurements via remote sensing, which are often characterized by limited precision, low reliability, and insufficient spatial resolution. In this paper, we introduce He3-Seeker, an active robotic exploration method for helium-3 distribution mapping. First, we provide a formal definition of the active helium-3 exploration problem. We then develop the He3-Seeker framework, which is conceptually based on multi-point drilling, sampling, and in situ analysis. In particular, we use robotic information planning to guide autonomous robot navigation and active sensing. Additionally, to evaluate the proposed algorithm, we introduce a reliable method for generating reference data of lunar helium-3 distribution based on low-resolution orbital remote sensing measurements. Simulation experiments verify that He3-Seeker enables fast, high-fidelity helium-3 distribution for resource exploration tasks.
Overview of the He3-Seeker system architecture, highlighting the integration of continuous spatial field modeling, informative path planning, and physical ground truth reference generation.
Employs Gaussian Process Regression (GPR) with Squared Exponential kernels to model continuous He-3 abundance fields, estimating dense mean maps and epistemic uncertainty under sparse physical measurements.
Utilizes an online RRT*-based planner optimizing a joint utility function balancing differential entropy information gain against traversal cost, while navigating hazardous topographic DEMs.
Lunar landing site benchmark environments generated for algorithm evaluation: Taurus-Littrow (Region T1) and Hadley Rille (Region T2).
@inproceedings{li2026he3seeker,
title = {He3-Seeker: Robotic Information Planning for Lunar Helium-3 Distribution Mapping},
author = {Li, Dong and Zheng, Yujie and Cao, Chengdeng and Teng, Siyu and Li, Yuchen and Gao, Yang and Chen, Long},
booktitle = {International Conference on Space Robotics (iSpaRo)},
year = {2026}
}