Industrial robots are precise and efficient at performing repetitive tasks. However, robots lack the ability to recognize and manipulate objects. They rely on human operators to translate the desired task into a set of operations that it can perform. The research area of bin-picking aims to provide robots with the ability to manipulate randomly ordered objects in unstructured environments. This research focuses on developing a robust vision guided robotic block pick-up and stacking system. We use binary markers to aid in block identification and localization, a custom 3D-printed gripper for robust grasping, and planning algorithms to determine the grasp sequence. By integrating a low-cost webcam with an industrial robot, our system is able to observe the block locations in a random pile, determine the appropriate response necessary to grasp, and sequence to remove blocks from a pile.