Includes bibliographical references and index.

The book offers the reader the insight on artificial neural networks for giving a robot a high level of autonomy tasks such as navigation, object recognition, and clustering, with real-time implementations. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures to solve different kinds of problems encountered in autonomous navigation and object recognition problems. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control.