1. Range Imaging and Pose Estimation of Non-Cooperative Targets using Structured Light Dr Frank Pipitone, Head, Sensor Based Systems Group Navy Center for Applied Research in Artificial Intelligence NRL Code 5515

2. Structured Light Range Imaging Technology Conceptual Depiction Structured Light Source CCD Camera Reflected Light Pursuer Spacecraft Target Spacecraft Pursuer illuminates target with structured light and captures the reflected light on the CCD focal plane array. A range image of the illuminated surface is then generated using triangulation. Outgoing Light

3. Structured Light Range Imaging Technology Moving Correlation Code Triangulation

4. Structured Light Range Imaging Technology Triangulation Geometry Mask scanning motion allows range mapping of all accessible points

5. Structured Light Range Imaging Technology First Prototype Correlation Scanner Range Image (resolution ~ 0.1 mm at 1 ft) Desktop Layout Scanner Camera Mask Target

6. Structured Light Range Imaging Technology Second Prototype Correlation Scanner

7. Structured Light Range Imaging Technology Conceptual Design of Spacecraft Coded Mask Scanner Housing Clear Window Motor Drive Shaft Coded Mask Outer Race Encoder Rotor Inner Race Slit Bulb Turret Stator Base Characteristics Light Source Xenon flash lamp Slit 3 cm x 1 mm Integral Mask/Optical EncoderEighth Order DeBruijn Sequence Mask size, height x arc width3 cm x 12.56 cm Radial distance to slit10 cm Encoder error< 0.01 deg Scan wheel10 rpm + 0.1 %, < 25 cm DIA

8. Pose Estimation Using Tripod Operators Description and Key Properties Twelve Point Tripod Operator Tripod operators are a mathematical procedure for rapid recognition and localization of arbitrary surface shapes in range images. TO’s consist of a set of equilateral rigid triangles joined on one or more sides, with each joint characterized by a hinge angle. Random application to a scene is achieved by “flexing” the 9 hinges computationally until all vertices lie on the surface Three parameters specify a placement: x A, y A,  so a 3D manifold (at most) of points in 9-space serves as signature of shape Only 12 vertex points are used; most pixels never visited Upon comparison with a trained model, the solution consists of shape recognition and 6 DOF pose estimation, typically occurring in tens of milliseconds

9. Pose Estimation Using Tripod Operators Test Examples of Feature Recognition Large torus is detected in 8 placements on a synthetic image 90 degree dihedral is detected in 8 placements on a LIDAR image with TO edge length of 7 cm Each detection took approximately 30 milliseconds

10. Pose Estimation Using Tripod Operators Industrial CRADA with NRL, Ford, and Perceptron Range image of a Ford torque converter generated with a Perceptron LASAR scanner Feature recognition and pose is obtained using 12-point Tripod Operators developed at NRL Robot manipulator grabs torque converter from pallet based on 5-state pose estimation

11. Structured Light Range Imaging & Pose Estimation Block Diagram Auto GN & C Range Imaging Control Electronics Timing Electronics Wheel Drive Electronics Scan Wheel Flash Electronics Power Supply Optical Position Encoder Xenon Flash Tube Slit Structured Light Projector Mask Target Camera Frame Grabber Processor Interpret code for each pixel Generate 3-D surface image Apply tripod operator randomly over image Match tripod operators to model signature Match yields identity and pose of target object relative to imager Strobe Pose Estimation Wheel Speed Control Synchronization

12. Structured Light Range Imaging & Pose Estimation Advantages 4 Enables accurate generation of three-dimensional surface models for any space object, including cooperative and non-cooperative satellites and natural bodies 4 Provides full aspect knowledge of target from many partial views (a complete range image is obtained by meshing partial images) 4 Six-state pose estimation is derived for an arbitrary surface shape without the need for target fiducial features, protuberances, or reflective patterns 4 Complete range image, feature recognition, and pose estimation are obtained in a fraction of a second 4 Potential application to a wide variety of complex problems such as AR&C, inspection, surveillance, repair, and assembly