3D Imaging for Autonomous Robots: Improving Machine Vision Using Time-of-Flight Cameras

One crucial aspect for autonomous vehicle navigation is to have the capability of detecting the surrounding terrain in a very fast and robust manner. Recently developed 3D Time-of-Flight cameras have an enormous potential for mobile robotic applications in particular for mapping and navigation tasks. This book presents the implementation of a Swiss Ranger SR3000 TOF camera with a real time algorithm developed in LabVIEW, which was incorporated into the university Intelligent Ground Vehicle cognition software. The algorithm utilizes a new approach of programming with Dynamic Link Library nodes in LabVIEW to communicate with the camera and is capable to filter, reduce, rotate, transform, read and write the incoming data and then to perform basic feature extraction on spherical objects. After the removal of the ground plane data, spherical objects lying on the floor were successfully detected. This work will help students who are working on a robotics project majoring in disciplines such as computer science, mechanical engineering or electronics to be one step ahead at their project, or any other enthusiasts who are interested in building their own machine vision for autonomous robots