Toward an Autonomous Lunar Landing Based on Low-Speed Optic Flow Sensors

Abstract

For the last few decades, growing interest has returned to the quite challenging task of the autonomous lunar landing. Soft landing of payloads on the lunar surface requires the development of new means of ensuring safe descent with strong final conditions and aerospace-related constraints in terms of mass, cost and computational resources. In this paper, a two-phase approach is presented: first a biomimetic method inspired from the neuronal and sensory system of flying insects is presented as a solution to perform safe lunar landing. In order to design an autopilot relying only on optic flow (OF) and inertial measurements, an estimation method based on a two-sensor setup is introduced: these sensors allow us to accurately estimate the orientation of the velocity vector which is mandatory to control the lander's pitch in a quasi-optimal way with respect to the fuel consumption. Secondly a new low-speed Visual Motion Sensor (VMS) inspired by insects' visual systems performing local angular 1-D speed measurements ranging from 1.5 • /s to 25 • /s and weighing only 2.8 g is presented. It was tested under free-flying outdoor conditions over various fields onboard an 80 kg unmanned helicopter. These preliminary results show that the optic flow measured despite the complex disturbances encountered closely matched the ground-truth optic flow.

Experimental results of a Terrain Relative Navigation algorithm using a simulated lunar scenario

“…The simulation of the final phase of the landing trajectory is of crucial importance, therefore software tools [4,5] and hardware facilities [6,7] have been used to test the algorithms. Optical Navigation seems to be one of the most promising techniques, see [8][9][10]; in this complex field, the concept of Optical Flow deserves a primary role [11,12].…”