Current planetary rovers operate at traverse speeds of approximately 10 cm/s, fundamentally limiting exploration efficiency. This work presents integrated AI systems which significantly improve autonomy through three components: (i) the FASTNAV Far Obstacle Detector (FOD), capable of facilitating sustained 1.0 m/s speeds via computer vision-based obstacle detection; (ii) CISRU, a multi-robot coordination framework enabling human-robot collaboration for in-situ resource utilisation; and (iii) the ViBEKO and AIAXR deep learning-based terrain classification studies. Field validation in Mars analogue environments demonstrated these systems at Technology Readiness Level 4, providing measurable improvements in traverse speed, classification accuracy, and operational safety for next-generation planetary missions.
@article{arxiv.2510.05985,
title = {AI-Enabled Capabilities to Facilitate Next-Generation Rover Surface Operations},
author = {Cristina Luna and Robert Field and Steven Kay},
journal= {arXiv preprint arXiv:2510.05985},
year = {2025}
}
Comments
Paper for 18th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA), presented on October 7th at Leiden, Netherlands