Planetary landers have, in the past, relied on physical means to protect the payload from the shock of impact on the surface [1]. These landers, starting their descent from orbit with their initial position only known to a few kilometres, were not required to land at a particular landing spot, but only to land safely.Today, much more knowledge, obtained from earlier landings and high-resolution orbiting instruments, is available about the surfaces of some planets than was available when previous landers were designed.Missions are becoming more demanding in terms of the accuracy of landing and significant effort is now focused on the design of surface relative navigation systems.Surface relative navigation requires a sensor that can pick out features or landmarks on the surface and use these to track the position of the spacecraft relative to the surface -passive and active vision-based navigation sensors are currently being developed.The testing of these sophisticated sensors, in particular the image processing parts, required the development of a realistic, large-scale test bed, representative of the real planet's surface. Physical modelling was not able to meet the needs of the sensor testing, so a virtual reality tool has been developed.PANGU (Planet and Asteroid Natural Scene Generation Utility) is a software tool for simulating and visualising the surface of various planetary bodies. It has been designed to support the development of planetary landers that use computer vision to navigate towards the surface and to avoid any obstacles near the landing site. PANGU can be used to generate an artificial surface representative of cratered planets and to provide images of the simulated planet. When given the position and orientation of a spacecraft above the planet's surface, PANGU responds by producing an image of the surface from that view point. Current research is extending the capabilities of PANGU so that Martian surfaces and asteroids can also be simulated. This paper describes the PANGU simulation tool in detail and provides example images of the simulated surface as seen from a descending planetary lander. Downloaded by 178.174.154.35 on June 21, 2016 | http://arc.aiaa.org |

We present an autonomous visual landmark recognition and pose estimation algorithm designed for use in navigation of spacecraft around small asteroids. Landmarks are selected as generic points on the asteroid surface that produce strong Harris corners in an image under a wide range in viewing and illumination conditions; no particular type of morphological feature is required. The set of landmarks is triangulated to obtain a tightly fitting mesh representing an optimal low resolution model of the natural asteroid shape, which is used onboard to determine the visibility of each landmark and enables the algorithm to work with highly concave bodies. The shape model is also used to estimate the centre of brightness of the asteroid and eliminate large translation errors prior to the main landmark recognition stage. The algorithm works by refining an initial estimate of the spacecraft position and orientation. Tests with real and synthetic images show good performance under realistic noise conditions. Using simulated images, the median landmark recognition error is 2m, and the error on the spacecraft position in the asteroid body frame is reduced from 45m to 21m at a range of 2km from the surface. With real images the translation error at 8km to the surface increases from 107m to 119m, due mainly to the larger range and lack of sensitivity to translations along the camera boresight. The median number of landmarks detected in the simulated and real images is 59 and 44 respectively. This algorithm was partly developed and tested during industrial studies for the European Space Agency’s Marco Polo-R asteroid sample return mission.

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Abstract-Spacecraft exploration of asteroids presents a variety of autonomous navigation challenges that can be aided by virtual models to test and develop guidance and hazard avoidance systems. This paper describes the extension and application of graphics techniques to create high-resolution, virtual asteroid models to simulate cameras and other spacecraft sensors approaching and descending towards asteroids. A scalable model structure with evenly spaced vertices is specified to simplify terrain modeling, avoid distortion at the poles and enable triangle strip definition for efficient rendering. The base asteroid models are created using both a two-phase Poisson faulting technique and Perlin noise. Realistic asteroid surfaces are created by adding synthetic crater models adapted from lunar terrain simulation and multi-resolution boulders to the base models. The synthetic asteroids are evaluated by comparison with real asteroid images, slope distributions, and by applying a surface relative feature tracking algorithm to the models.