Proximity Navigation Near and Mapping of Asteroids

Sensor fusion algorithms are proposed that enable proximity navigation and mapping of an unknown space object, such as an asteroid. The sensors envisioned are a range sensor (Flash LIDAR), and a synchronized and co-registered HD video camera, and an IMU. The transition from intermediate to close proximity is considered wherein the observability early-on allows only the 3DOF range vector to be determined, and in close proximity where the full 6DOF relative pose is observeable and the object geometry can be recursively learned/estimated. Our algorithms are novel because of (i) unique utilization of sensor field overlap-induced information redundancy to eliminate poor features and retain the most consistent features on the object based on statistical hypothesis-testing and (ii) utilization of a recently discovered way to rigorously linearize the least square fusion of two overlapping point clouds, without approximation. End-to-end experiments in our laboratory http://lasr.tamu.edu/ are proposed to accelerate maturation and evaluation of the technology.

Our algorithms are novel because of (i) unique utilization of sensor field overlap-induced information redundancy to eliminate poor features and retain the most consistent features on the object based on statistical hypothesis-testing and (ii) utilization of a recently discovered way to rigorously linearize the least square fusion of two overlapping point clouds, without approximation.

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