Risk-Aware Autonomous EVA Mission Planning and Dynamic Replanning for Planetary Analog Missions

This paper presents a risk-aware autonomous Extravehicular Activity (EVA) mission planning and dynamic replanning framework for planetary analog missions. The proposed framework integrates terrain hazard assessment, consumable-depletion risk, communication constraints, and real-time mission monitoring using a risk-aware Informed RRT* path planner. The framework is evaluated through simulation informed by a seven-EVA analog mission conducted in the Rann of Kutch, India. It investigates how autonomous replanning responds to unexpected terrain hazards, accelerated oxygen depletion, changing mission priorities, and errors in consumable-consumption estimates. The study demonstrates the potential of dynamic replanning and online oxygen-consumption estimation to improve astronaut safety, preserve consumable reserves, and maintain mission objectives during planetary surface exploration. The findings also identify limitations associated with synthetic terrain maps, wearable-derived physiological estimates, and single-participant data. This research contributes to the development of autonomous EVA operations and intelligent mission-planning systems for future lunar and Martian exploration.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-04
DOI
https://doi.org/10.5281/zenodo.23953724
Primary Topic
Space Exploration and Technology
Type
preprint
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Risk-Aware Autonomous EVA Mission Planning and Dynamic Replanning for Planetary Analog Missions

Inchara Nataraj
Zenodo (CERN European Organization for Nuclear Research)
Space Exploration and Technology
preprint

Risk-Aware Autonomous EVA Mission Planning and Dynamic Replanning for Planetary Analog Missions

Inchara Nataraj
preprint en

Abstract

This paper presents a risk-aware autonomous Extravehicular Activity (EVA) mission planning and dynamic replanning framework for planetary analog missions. The proposed framework integrates terrain hazard assessment, consumable-depletion risk, communication constraints, and real-time mission monitoring using a risk-aware Informed RRT* path planner. The framework is evaluated through simulation informed by a seven-EVA analog mission conducted in the Rann of Kutch, India. It investigates how autonomous replanning responds to unexpected terrain hazards, accelerated oxygen depletion, changing mission priorities, and errors in consumable-consumption estimates. The study demonstrates the potential of dynamic replanning and online oxygen-consumption estimation to improve astronaut safety, preserve consumable reserves, and maintain mission objectives during planetary surface exploration. The findings also identify limitations associated with synthetic terrain maps, wearable-derived physiological estimates, and single-participant data. This research contributes to the development of autonomous EVA operations and intelligent mission-planning systems for future lunar and Martian exploration.

Zenodo (CERN European Organization for Nuclear Research)
R.V. College of Engineering (IN)
Space Exploration and Technology
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