Research/ PLANETARY ROBOTICS
Autonomous mission planning and biosignatures image detection for planetary exploration with drones
Julian Galvez-Serna
Autonomy, Task Planning & OperationsOpenAlex topic: AI-based Problem Solving and Planning · Learning-based MethodsOpenAlex topic: Reinforcement Learning in Robotics
This thesis reviews and expands current drone navigation and mission planning approaches for planetary exploration missions with drones, focusing on Mars and the autonomy needed. Recognising the importance of astrobiology in Mars exploration, this thesis proposes a high-level mission planning architecture for planetary exploration based on AI techniques such as reinforced learning, deep learning and computer vision focusing on missions to detect life signatures or biosignatures on planetary surfaces. The tools and ideas developed in this thesis aim to enable drones to help us answer the question, are we alone in the universe?