Robust approximation of image illumination direction in a segmentation-based crater detection algorithm for spacecraft navigation

Maass, Bolko

doi:10.1007/s12567-016-0129-1

Cited by 8 publications

(8 citation statements)

References 11 publications

(8 reference statements)

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“…In every camera image that is to be used for navigation, craters need to be detected to be matched to map craters. The imageprocessing algorithms that the CNav system uses for this purpose have been discussed in [18,19]; in this section, we will therefore only very briefly summarize the salient points.…”

Section: Crater Detectionmentioning

confidence: 99%

Crater Navigation System for Autonomous Precision Landing on the Moon

Maass

Woicke

Oliveira

et al. 2020

Journal of Guidance, Control, and Dynamics

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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.

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Section: Crater Detectionmentioning

confidence: 99%

Crater Navigation System for Autonomous Precision Landing on the Moon

Maass

Woicke

Oliveira

et al. 2020

Journal of Guidance, Control, and Dynamics

Self Cite

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“…Next to this regular drift removal over crater fields, larger corrections after phases where no craters were visible are of great value. The crater detection is based on the extraction and matching of adjacent areas of above-and below-average brightness that model the reflection and shadow of typical crater interiors under illumination [21,22].…”

Section: Crater Navigationmentioning

confidence: 99%

ATON (Autonomous Terrain-based Optical Navigation) for exploration missions: recent flight test results

et al. 2018

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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

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“…• Crater Navigation: The Crater Navigation module detects impact craters in the camera images, and matches each crater detection to an element from a static crater catalog referenced in Moon-fixed coordinates. From that correspondence, a Moon-fixed position can be computed [6], [7].…”

Section: Dlr's Project Atonmentioning

confidence: 99%

Using an UAV for testing an autonomous terrain-based optical navigation system for lunar landing

Ammann

Theil

2018

2018 IEEE Aerospace Conference

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This paper presents the application of a rotary wing Unmanned Aerial Vehicle (UAV) as a testbed for the optical navigation system developed in the project "Autonomous Terrainbased Optical Navigation" (ATON) of the German Aerospace Center (DLR). Since using optical sensor data in navigation systems for exploration missions is a promising technology, many projects have focused on the development of such navigation systems. To allow autonomous operation of these developed navigation technologies in the targeted environment extensive testing is necessary for achieving an appropriate grade of reliability. A review of the current approaches for true-scale testing of optical navigation systems for lunar or planetary landing missions is conducted, and the proposed testing methodology is motivated. The paper describes the development steps necessary to conduct closed-loop real-time flight tests using a rotary wing UAV. This includes the sensor configuration, preparation of the flight test area and ground truth generation. Finally, the resulting navigation performance of the ATON navigation system in the closed-loop real-time flight tests is presented.

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Robust approximation of image illumination direction in a segmentation-based crater detection algorithm for spacecraft navigation

Cited by 8 publications

References 11 publications

Crater Navigation System for Autonomous Precision Landing on the Moon

Crater Navigation System for Autonomous Precision Landing on the Moon

ATON (Autonomous Terrain-based Optical Navigation) for exploration missions: recent flight test results

Using an UAV for testing an autonomous terrain-based optical navigation system for lunar landing

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