A Deep Learning Approach to Lunar Rover Global Path Planning Using Environmental Constraints and the Rover Internal Resource Status

A Deep Learning Approach to Lunar Rover Global Path Planning Using Environmental Constraints and the Rover Internal Resource Status

This research proposes a novel approach to global path and resource planning for lunar rovers. The proposed method incorporates a range of constraints, including static, time-variant, and path-dependent factors related to environmental conditions and the rover’s internal resource status. These const...

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Bibliographic Details
Main Authors: Toshiki Tanaka, Heidar Malki
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Sensors
Subjects:
path planning
planetary rover
lunar rover
reinforcement learning
Online Access:https://www.mdpi.com/1424-8220/24/3/844

Internet

https://www.mdpi.com/1424-8220/24/3/844

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