Controlled illumination for perception and manipulation of Lambertian objects

Controlling illumination can generate high quality information about object surface normals and depth discontinuities at a low computational cost. In this work we demonstrate a robot workspace-scaled controlled illumination approach that generates high quality information for table top scale objects for robotic manipulation. With our low angle of incidence directional illumination approach we can precisely capture surface normals and depth discontinuities of Lambertian objects. We demonstrate three use cases of our approach for robotic manipulation. We show that 1) by using the captured information we can perform general purpose grasping with a single point vacuum gripper, 2) we can visually measure the deformation of known objects, and 3) we can estimate pose of known objects and track unknown objects in the robot's workspace. Additional demonstrations of the results presented in the work can be viewed on the project webpage https://anonymousprojectsite.github.io/.