Crowdsourcing the construction of a 3D object recognition database for robotic grasping

Object recognition and manipulation are critical in enabling robots to interact with objects in a household environment. Construction of 3D object recognition databases is time and resource intensive, often requiring specialized equipment, and is therefore difficult to apply to robots in the field. We present a system for constructing object models for 3D object recognition and manipulation made possible by advances in web robotics. The database consists of point clouds generated using a novel iterative point cloud registration algorithm, which includes the potential to encode manipulation data and usability characteristics. We validate the system with a crowdsourcing user study and object recognition system designed to work with our object recognition database.