Autonomous mission planning for planetary surface exploration using a team of micro rovers

One of the fundamental limiting factors in planetary exploration is the level of autonomy achieved by planetary exploration rovers. This study proposes a novel methodology for the coordination of an autonomous multi-robot team that evaluates efficient exploration routes in Jezero crater, Mars. A map is generated consisting of a 3D terrain model, traversability analysis, and probability distribution map of points of scientific interest. A three-stage mission planner generates an efficient team-wide route, which maximises the accumulated probability of identifying points of interest. A 4D RRT* algorithm is used to determine smooth and flat paths for individual rovers, following the team-wide route planner, and prioritized planning is used to coordinate a safe set of individual paths. The above methodology is shown to coordinate safe and efficient rover paths, which ensure the rovers remain within their nominal pitch and roll limits throughout operation.

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Publication Details

Journal
Frontiers in Robotics and AI
Published
2025-04-09
DOI
https://doi.org/10.3389/frobt.2025.1565173
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
2.55
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article

Autonomous mission planning for planetary surface exploration using a team of micro rovers

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2 citations
Frontiers in Robotics and AI
Robotic Path Planning Algorithms
2.55
article

Autonomous mission planning for planetary surface exploration using a team of micro rovers

Douglas Thomson, Sarah Swinton, Euan McGookin, David Anderson, Jan‐Hendrik Ewers
article en
2 citations

Abstract

One of the fundamental limiting factors in planetary exploration is the level of autonomy achieved by planetary exploration rovers. This study proposes a novel methodology for the coordination of an autonomous multi-robot team that evaluates efficient exploration routes in Jezero crater, Mars. A map is generated consisting of a 3D terrain model, traversability analysis, and probability distribution map of points of scientific interest. A three-stage mission planner generates an efficient team-wide route, which maximises the accumulated probability of identifying points of interest. A 4D RRT* algorithm is used to determine smooth and flat paths for individual rovers, following the team-wide route planner, and prioritized planning is used to coordinate a safe set of individual paths. The above methodology is shown to coordinate safe and efficient rover paths, which ensure the rovers remain within their nominal pitch and roll limits throughout operation.

Frontiers in Robotics and AIVol. 12
University of Glasgow (GB)
Openalex Percentile: Top 11%
Robotic Path Planning Algorithms
2.55
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