Stereoscopic eye in hand active machine vision for real-time adaptive robot arm guidance.

This thesis describes the design, development and implementation of a robot mounted active stereo vision system for adaptive robot arm guidance. This provides a very flexible and intelligent system that is able to react to uncertainty in a manufacturing environment. It is capable of tracking and determining the 3D position of an object so that the robot can move towards, and intercept, it. Such a system has particular applications in remotely controlled robot arms, typically working in hostile environments. The stereo vision system is designed on mechatronic principles and is modular, light-weight and uses state-of-the-art dc servo-motor technology. Based on visual information, it controls camera vergence and focus independently while making use of the flexibility of the robot for positioning. Calibration and modelling techniques have been developed to determine the geometry of the stereo vision system so that the 3D position of objects can be estimated from the 2D camera information. 3D position estimates are obtained by stereo triangulation. A method for obtaining a quantitative measure of the confidence of the 3D position estimate is presented which is a useful built-in error checking mechanism to reject false or poor 3D matches. A predictive gaze controller has been incorporated into the stereo head control system. This anticipates the relative 3D motion of the object to alleviate the effect of computational delays and ensures a smooth trajectory. Validation experiments have been undertaken with a Puma 562 industrial robot to show the functional integration of the camera system with the robot controller. The vision system is capable of tracking moving objects and the information this provides is used to update command information to the controller. The vision system has been shown to be in full control of the robot during a tracking and intercept duty cycle