Proposing new path-planning metrics for operating rovers on Mars.

Area of Science:

• Planetary Science
• Robotics
• Artificial Intelligence

Background:

• Mars rover operations require sophisticated path planning for mission success.
• Path planning algorithms assist operators by generating candidate paths based on cost functions.
• Traditional metrics like distance traveled, solution runtime, and expanded nodes are commonly used.

Purpose of the Study:

• To analyze the utility of traditional path-planning metrics in challenging, partially known Martian terrain.
• To review existing metrics using two path-planning algorithms on real Mars maps.
• To propose novel metrics for assessing paths in real-world Mars rover applications.

Main Methods:

• Review of established path-planning metrics.
• Application of two path-planning algorithms on real Mars terrain data.
• Analysis of metric performance in complex environments.

Main Results:

• Traditional metrics may not fully capture the complexities of path selection in unknown Martian terrains.
• Evaluation of the effectiveness of distance, runtime, and node expansion metrics.
• Identification of limitations in current path assessment methods.

Conclusions:

• Existing path-planning metrics require re-evaluation for extraterrestrial applications.
• New metrics are proposed to better assess path suitability for Mars rovers.
• Enhanced path assessment is crucial for efficient and safe Mars exploration.