Engineering autonomous and intelligent space systems such as rovers or satellites that are capable of robust, long-term operations with little to no human-intervention is a challenging exercise. Advanced perception, planning and decision-making abilities need to be composed both on a technical and conceptual level into an overall architecture without sacrificing functional and non-functional requirements such as reliability, availability and robustness. The main objective of this course is not only to raise awareness of the impact of functional and architectural design decisions, but also to endow students with the knowledge to describe, analyze and develop dependable space systems with a high-degree of autonomy as required by space scenarios operating over a long-period of time in challenging and remote environments. This course will combine experiments on virtual and real environments using ROS. The real experiments are planned to be done at the LunaLab facility.
Outcome:
After completing the course students will be able to: Identify and select the right sensor(s) for the different applications Extract data from the sensors using ROS Basic uses for image and cloud points processing algorithms Control of a lunar rover vehicle Use basic path planning algorithms on ROS Self-localization on an unknown environment Improve odometry using filtering algorithms
