Language And Learning For Robots
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Deep Learning for Robot Perception and Cognition
Author: Alexandros Iosifidis
language: en
Publisher: Academic Press
Release Date: 2022-02-04
Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis
Artificial Vision and Language Processing for Robotics
Author: Álvaro Morena Alberola
language: en
Publisher: Packt Publishing Ltd
Release Date: 2019-04-30
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.
Designing, Constructing, and Programming Robots for Learning
The field of robotics in a classroom context has seen an increase in global momentum recently because of its positive contributions in the teaching of science, technology, engineering, mathematics (STEM) and beyond. It is argued that when robotics and programming are integrated in developmentally appropriate ways, cognitive skill development beyond STEM can be achieved. The development of educational robotics has presented a plethora of ways in which students can be assisted in the classroom. Designing, Constructing, and Programming Robots for Learning highlights the importance of integrating robotics in educational practice and presents various ways for how it can be achieved. It further explains how 21st century skills and life skills can be developed through the hands-on experience of educational robotics. Covering topics such as computational thinking, social skill enhancement, and teacher training, this text is an essential resource for engineers, educational software developers, teachers, professors, instructors, researchers, faculty, leaders in educational fields, students, and academicians.