Toward Guaranteed Illumination Models for Non-Convex Objects

Illumination variation remains a central challenge in object detection and recognition. Existing analyses of illumination variation typically pertain to convex, Lambertian objects, and guarantee quality of approximation in an average case sense. We show that it is possible to build V(vertex)-description convex cone models with worst-case performance guarantees, for non-convex Lambertian objects. Namely, a natural verification test based on the angle to the constructed cone guarantees to accept any image which is sufficiently well-approximated by an image of the object under some admissible lighting condition, and guarantees to reject any image that does not have a sufficiently good approximation. The cone models are generated by sampling point illuminations with sufficient density, which follows from a new perturbation bound for point images in the Lambertian model. As the number of point images required for guaranteed verification may be large, we introduce a new formulation for cone preserving dimensionality reduction, which leverages tools from sparse and low-rank decomposition to reduce the complexity, while controlling the approximation error with respect to the original cone

Apollo experience report: Simulation of manned space flight for crew training

Through space-flight experience and the development of simulators to meet the associated training requirements, several factors have been established as fundamental for providing adequate flight simulators for crew training. The development of flight simulators from Project Mercury through the Apollo 15 mission is described. The functional uses, characteristics, and development problems of the various simulators are discussed for the benefit of future programs

A Flexible Image Processing Framework for Vision-based Navigation Using Monocular Image Sensors

On-Orbit Servicing (OOS) encompasses all operations related to servicing satellites and performing other work on-orbit, such as reduction of space debris. Servicing satellites includes repairs, refueling, attitude control and other tasks, which may be needed to put a failed satellite back into working condition. A servicing satellite requires accurate position and orientation (pose) information about the target spacecraft. A large quantity of different sensor families is available to accommodate this need. However, when it comes to minimizing mass, space and power required for a sensor system, mostly monocular imaging sensors perform very well. A disadvantage is- when comparing to LIDAR sensors- that costly computations are needed to process the data of the sensor. The method presented in this paper is addressing these problems by aiming to implement three different design principles; First: keep the computational burden as low as possible. Second: utilize different algorithms and choose among them, depending on the situation, to retrieve the most stable results. Third: Stay modular and flexible. The software is designed primarily for utilization in On-Orbit Servicing tasks, where- for example- a servicer spacecraft approaches an uncooperative client spacecraft, which can not aid in the process in any way as it is assumed to be completely passive. Image processing is used for navigating to the client spacecraft. In this specific scenario, it is vital to obtain accurate distance and bearing information until, in the last few meters, all six degrees of freedom are needed to be known. The smaller the distance between the spacecraft, the more accurate pose estimates are required. The algorithms used here are tested and optimized on a sophisticated Rendezvous and Docking Simulation facility (European Proximity Operations Simulator- EPOS 2.0) in its second-generation form located at the German Space Operations Center (GSOC) in Weßling, Germany. This particular simulation environment is real-time capable and provides an interface to test sensor system hardware in closed loop configuration. The results from these tests are summarized in the paper as well. Finally, an outlook on future work is given, with the intention of providing some long-term goals as the paper is presenting a snapshot of ongoing, by far not yet completed work. Moreover, it serves as an overview of additions which can improve the presented method further