CAD-based robot vision

Abstract

This article explains that model-based recognition, programming, and control of manipulators is one of the key paradigms in computer vision and robotics. To recognize and manipulate objects, the authors concern themselves only with expected objects in the task environment of a robot. They use data from multiple sensors (such as television, range, force, torque, touch, etc.) and a priori knowledge (object models, strategies for sensing, recognition and manipulation, etc.) to equip the robot with intelligence so that it can sense, plan, and manipulate objects in its environment. As shown, the basic computational model for object recognition and manipulation is strongly goal-directed. Their goal is the capability to acquire a variety of 3D object models automatically with all the desired information for recognition and manipulation. CAD has provided new opportunities and challenges for the use of models of 3D objects. Using the available 3D models of objects, one can plan recognition and manipulation strategies during the off-line phase and do efficient real-time recognition and manipulation during the runtime phase.