Artificial Vision For Robots

Download or read book Artificial Vision for Robots written by I. Aleksander and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: I. ALEKSANDER Department of Electrical Engineering and Electronics BruneI University, England The three key words that appear in the title of this book need some clarification. First, how far does the word robot reach in the context of indus trial automation? There is an argument maintaining that this range is not fixed, but increases with advancing technology. The most limited definition of the robot is also the earliest. The history is worth following because it provides a convincing backdrop to the central point of this book: vision is likely to epitomize the technolo gical advance, having the greatest effect in enlarging the definition and range of activity of robots. In the mid 1950s it was foreseen that a purely mechanical arm-like device could be used to move objects between two fixed locations. This was seen to be cost-effective only if the task was to remain fixed for some time. The need to change tasks and therefore the level of programmability of the robot was a key issue in the broadening of robot activities. Robots installed in industry in the early 1960s derived their programmability from a device called apinboard. Ver tical wires were energized sequentially in time, while horizontal wires, when energized, would trigger off elementary actions in the manipulator arm. The task of reprogramming was a huge one, as pins had to be reinserted in the board, connecting steps in time with robot actions.

Download or read book Artificial Vision for Mobile Robots written by Nicholas Ayache and published by MIT Press. This book was released on 1991 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: To give mobile robots real autonomy, and to permit them to act efficiently in a diverse, cluttered, and changing environment, they must be equipped with powerful tools for perception and reasoning. Artificial Vision for Mobile Robots presents new theoretical and practical tools useful for providing mobile robots with artificial vision in three dimensions, including passive binocular and trinocular stereo vision, local and global 3D map reconstructions, fusion of local 3D maps into a global 3D map, 3D navigation, control of uncertainty, and strategies of perception. Numerous examples from research carried out at INRIA with the Esprit Depth and Motion Analysis project are presented in a clear and concise manner. Nicolas Ayache is Research Director at INRIA, Le Chesnay, France. Contents. General Introduction. Stereo Vision. Introduction. Calibration. Image Representation. Binocular Stereo Vision Constraints. Binocular Stereo Vision Algorithms. Experiments in Binocular Stereo Vision. Trinocular Stereo Vision, Outlook. Multisensory Perception. Introduction. A Unified Formalism. Geometric Representation. Construction of Visual Maps. Combining Visual Maps. Results: Matching and Motion. Results: Matching and Fusion. Outlook.

Download or read book Robot Vision written by Berthold Horn and published by MIT Press. This book was released on 1986 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Presents a solid framework for understanding existing work and planning future research."--Cover.

Download or read book Robotic Vision: Technologies for Machine Learning and Vision Applications written by Garcia-Rodriguez, Jose and published by IGI Global. This book was released on 2012-12-31 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed. Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.

Download or read book Artificial Vision and Language Processing for Robotics written by Álvaro Morena Alberola and published by Packt Publishing Ltd. This book was released on 2019-04-30 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key FeaturesStudy ROS, the main development framework for robotics, in detailLearn all about convolutional neural networks, recurrent neural networks, and roboticsCreate a chatbot to interact with the robotBook Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learnExplore the ROS and build a basic robotic systemUnderstand the architecture of neural networksIdentify conversation intents with NLP techniquesLearn and use the embedding with Word2Vec and GloVeBuild a basic CNN and improve it using generative modelsUse deep learning to implement artificial intelligence(AI)and object recognitionDevelop a simple object recognition system using CNNsIntegrate AI with ROS to enable your robot to recognize objectsWho this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.

Download or read book Computer Vision and Sensor-Based Robots written by C.H. Dodd and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal ofthe symposium, "Computer Vision and Sensor-Based Robots," held at the General Motors Research Laboratories on September 2S and 26, 1978, was to stimulate a closer interaction between people working in diverse areas and to discuss fundamental issues related to vision and robotics. This book contains the papers and general discussions of that symposium, the 22nd in an annual series covering different technical disciplines that are timely and of interest to General Motors as well as the technical community at large. The subject of this symposium remains timely because the cost of computer vision hardware continues to drop and there is increasing use of robots in manufacturing applications. Current industrial applications of computer vision range from simple systems that measure or compare to sophisticated systems for part location determination and inspection. Almost all industrial robots today work with known parts in known posi tions, and we are just now beginning to see the emergence of programmable automa tion in which the robot can react to its environment when stimulated by visual and force-touch sensor inputs. As discussed in the symposium, future advances will depend largely on research now underway in several key areas. Development of vision systems that can meet industrial speed and resolution requirements with a sense of depth and color is a necessary step.

Download or read book Robotics, Vision and Control written by Peter Corke and published by Springer. This book was released on 2011-09-05 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: The author has maintained two open-source MATLAB Toolboxes for more than 10 years: one for robotics and one for vision. The key strength of the Toolboxes provide a set of tools that allow the user to work with real problems, not trivial examples. For the student the book makes the algorithms accessible, the Toolbox code can be read to gain understanding, and the examples illustrate how it can be used —instant gratification in just a couple of lines of MATLAB code. The code can also be the starting point for new work, for researchers or students, by writing programs based on Toolbox functions, or modifying the Toolbox code itself. The purpose of this book is to expand on the tutorial material provided with the toolboxes, add many more examples, and to weave this into a narrative that covers robotics and computer vision separately and together. The author shows how complex problems can be decomposed and solved using just a few simple lines of code, and hopefully to inspire up and coming researchers. The topics covered are guided by the real problems observed over many years as a practitioner of both robotics and computer vision. It is written in a light but informative style, it is easy to read and absorb, and includes a lot of Matlab examples and figures. The book is a real walk through the fundamentals of robot kinematics, dynamics and joint level control, then camera models, image processing, feature extraction and epipolar geometry, and bring it all together in a visual servo system. Additional material is provided at http://www.petercorke.com/RVC