We present a complete vision guided robot system for model based 3D pose estimation and picking of singulated 3D objects. Our system employs a novel vision sensor consisting of a video camera surrounded by eight flashes (light emitting diodes). By capturing images under different flashes and observing the shadows, depth edges or silhouettes in the scene are obtained. The silhouettes are segmented into different objects and each silhouette is matched across a database of object silhouettes in different poses to find the coarse 3D pose. The database is pre-computed using a Computer Aided Design (CAD) model of the object. The pose is refined using a fully projective formulation [ACB98] of Lowe's model based pose estimation algorithm [Low91, Low87]. The estimated pose is transferred to robot coordinate system utilizing the handeye and camera calibration parameters, which allows the robot to pick the object. Our system outperforms conventional systems using 2D sensors with intensity-b...