Interest in autonomous planetary precision landing missions has been increasing in the scientific and engineering community, and is likely to continue to do so for the foreseeable future. As an enabling technology in the context of lunar landing, DLR, German Aerospace Center has been developing a terrain absolute navigation system that matches craters detected in image data to globally available lunar crater maps. The proposed Crater Navigation (CNav) system is adaptive, comprising three different crater matching methods that are specifically tailored to different navigation conditions encountered during the vehicle descent, so that it may be used as a stand-alone navigation sensor that can be closely integrated with a lander guidance, navigation, and control system to enable reliable absolute navigation throughout the entire descent phase of a mission. As robustness is a vital aspect to mission success, the CNav system includes verification mechanisms that ensure high dependability of the resulting navigation solution. This robustness is verified separately for all of the three different matching techniques presented in this paper. Closed-loop performance of the matchers is demonstrated as well, both for simulated image data sets, as for navigation camera images acquired during the Chinese Chang'e-3 landing mission. Successful uninterrupted estimation of the entire Chang'e-3 kinematic vehicle state during the powered descent until a final altitude of 350 m above ground, with neither known camera calibration nor inertial measurement unit data available, showcases the potential of the CNav system.
Since 2010 the German Aerospace Center (DLR) is working on the project ATON (Autonomous Terrain-based Optical Navigation). Its objective is the development of technologies which allow autonomous navigation of spacecraft in orbit around and during landing on celestial bodies like the Moon, planets, asteroids and comets. The project developed different image processing techniques and optical navigation methods as well as sensor data fusion. The setup-which is applicable to many exploration missions-consists of an inertial measurement unit (IMU), a laser altimeter, a star tracker and one or multiple navigation cameras. In the past years, several milestones have been achieved. It started with the setup of a simulation environment including the detailed simulation of camera images. This was continued by hardware-in-the-loop tests in the Testbed for Robotic Optical Navigation where images were generated by real cameras in a simulated downscaled lunar landing scene. Data was recorded
Accurate autonomous navigation capabilities are essential for future lunar robotic landing missions with a pinpoint landing requirement, since in the absence of direct line of sight to ground control during critical approach and landing phases, or when facing long signal delays the herein before mentioned capability is needed to establish a guidance solution to reach the landing site reliably. This paper focuses on the processing and evaluation of data collected from flight tests that consisted of scaled descent scenarios where the unmanned helicopter of approximately 85 kg approached a landing site from altitudes of 50 m down to 1 m for a downrange distance of 200 m. Printed crater targets were distributed along the ground track and their detection provided earth-fixed measurements. The Crater Navigation (CNav) algorithm used to detect and match the crater targets is an unmodified method used for real lunar imagery. We analyse the absolute position and attitude solutions of CNav obtained and recorded during these flight tests, and investigate the attainable quality of vehicle pose estimation using both CNav and measurements from a Tactical-grade Inertial Measurement Unit (IMU). The navigation filter proposed for this end corrects and calibrates the high-rate inertial propagation with the less frequent crater navigation fixes through a closed-loop, loosely coupled hybrid setup. Finally, the attainable accuracy of the fused solution is evaluated by comparison with the onboard ground-truth solution of a dual-antenna high-grade GNSS receiver. It is shown that the CNav is an enabler for building autonomous navigation systems with high quality and suitability for exploration mission scenarios.
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