LiDAR-Based Autonomous Landing on Asteroids: Algorithms, Prototyping and End-to-End Testing with a UAV-Based Satellite Emulator

Abstract

This paper presents an UAV emulation system allowing early hardware-in-the-loop testing for Terrain-Relative-Navigation (TRN) and autonomous guidance algorithm development in context of spacecraft landing on asteroids. The capabilities of this system are shown within the scope of an flight campaign in which a Light Detection And Ranging (LiDAR) only odometry navigation, hazard detection and avoidance system was implemented and tested. Furthermore, a special focus on a new asteroid analogue environment is given. The implemented TRN algorithms are based on the result of an Iterative Closest Point (ICP) algorithm and the adopted use of LiDAR range measurements as altimeter source. A Linear Kalman Filter (LKF) performs the necessary sensor fusion taking into account spacecraft control and asteroid environment forces. The TRN system is inspired by the NASA's MAVeN (minimal augmented state algorithm for vision-based navigation) algorithm used as TRN algorithm on the Mars UAV Ingenuity [24].