Performance Analysis for Visual Planetary Landing Navigation Using Optical Flow and DEM Matching

Abstract

Visual navigation for planetary landing vehicles shows many scientific and technical challenges due to inclined and rather high velocity approach trajectories, complex 3D environment and high computational requirements for real-time image processing. High relative navigation accuracy at landing site is required for obstacle avoidance and operational constraints. The current paper discusses detailed performance analysis results for a recently published concept of a visual navigation system, based on a mono camera as vision sensor and matching of the recovered and reference 3D models of the landing site. The recovered 3D models are being produced by real-time, instantaneous optical flow processing of the navigation camera images. An embedded optical correlator is introduced, which allows a robust and ultra high-speed optical flow processing under different and even unfavorable illumination conditions. The performance analysis is based on a detailed software simulation model of the visual navigation system, including the optical correlator as the key component for ultra-high speed image processing. The paper recalls the general structure of the navigation system and presents detailed end-to-end visual navigation performance results for a Mercury landing reference mission in terms of different visual navigation entry conditions, reference DEM resolution, navigation camera configuration and auxiliary sensor information.

Biomimetic optic flow sensing applied to a lunar landing scenario

“…The use of visual cues to guide spacecrafts' extraterrestrial soft landing performances has been recently investigated by several authors [24], [25], [3]. These systems either use visually assisted inertial navigation systems [25] or compute the optic flow by means of an optical correlator [3], [9] or extract information from a single camera [25], [26].…”

“…Apollo 11). Newer approaches include lidar techniques [1], [2] and visual techniques [3], [4], [5], [6], [7], [8], [9] often supported with inertial measurements. In addition, vision-based navigation plays a key role when it is required to detect an extraterrestrial target from afar.…”

An innovative navigation scheme of powered descent phase for Mars pinpoint landing

“…Vision-aided navigation can provide the horizontal position by detecting craters or other points of interest in the landing site and matching to a stored landmark database (Janschek et al, 2006;Pham et al, 2009;Yu et al, 2014;Wang et al, 2008). However, vision-aided navigation systems have some drawbacks: large amount of calculation, field of view constraints, and poor-performance measurements along the camera line-of-sight direction.…”

Vision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing

“…Unfortunately, [31] only contains a description of the overall system architecture, but no experimental validation. Finally, a vision-based EDL navigation system based on optic flow computation is proposed in [32]. This system extracts velocity information directly from the optic flow, as well as absolute pose information from matching a DEM of the landing site with a 3-D surface map computed from the optic flow.…”