AI-Driven Path Planning for Planetary Exploration Rovers
Year: 2023
Type: report
Abstract: This paper presents an AI-driven path planning approach for planetary exploration rovers, enabling autonomous navigation in complex and dynamic environments. We propose a framework that integrates machine learning algorithms with sensor data to enhance the rovers' ability to navigate challenging terrains. The study focuses on developing robust path planning algorithms that account for environmental variability, obstacles, and mission objectives. Experimental results validate the effectiveness of the proposed approach, demonstrating improved navigation efficiency and safety for planetary rovers. This research contributes to the advancement of autonomous systems for planetary exploration, paving the way for future missions on Mars and other celestial bodies.
Author: Kaliappan, Vishnu Kumar; KPR Institute of Engineering and Technology, India
Institution: KPR Institute of Engineering and Technology
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7035744798