Artificial Intelligence for Robotics - Second Edition - Govers, Francis X III

. .

Résumé :
..

Biographie:
Francis X. Govers III is an Associate Technical Fellow for Autonomy at Bell Textron, and chairman of the Textron Autonomy Council. He is the designer of over 30 unmanned vehicles and robots for land, sea, air, and space, including RAMSEE, the autonomous security guard robot. Francis helped lead the design of the International Space Station, the F-35 JSF Fighter, the US Army Future Combat Systems, and telemetry systems for NASCAR and IndyCar. He is an engineer, pilot, author, musician, artist, and maker. He received five outstanding achievement awards from NASA and recognition from Scientific American for World Changing Ideas. He has a Master of Science degree from Brandeis University and is a veteran of the US Air Force.

Sommaire:
Let an AI and robotics expert help you apply AI, systems engineering, and ML concepts to create smart robots capable of interacting with their environment and users, making decisions, and navigating autonomously Key Features - Gain a holistic understanding of robot design, systems engineering, and task analysis - Implement AI/ML techniques to detect and manipulate objects and navigate robots using landmarks - Integrate voice and natural language interactions to create a digital assistant and artificial personality for your robot - Purchase of the print or Kindle book includes a free PDF eBook Book Description Unlock the potential of your robots by enhancing their perception with cutting-edge artificial intelligence and machine learning techniques. From neural networks to computer vision, this second edition of the book equips you with the latest tools, new and expanded topics such as object recognition and creating artificial personality, and practical use cases to create truly smart robots. Starting with robotics basics, robot architecture, control systems, and decision-making theory, this book presents systems-engineering methods to design problem-solving robots with single-board computers. You'll explore object recognition using YOLO and genetic algorithms to teach your robot to identify and pick up objects, leverage natural language processing to give your robot a voice, and master neural networks to classify and separate objects and navigate autonomously, before advancing to guiding your robot arms using reinforcement learning and genetic algorithms. The book also covers path planning and goal-oriented programming to prioritize your robot's tasks, showing you how to connect all software using Python and ROS 2 for a seamless experience. By the end of this book, you'll have learned how to transform your robot into a helpful assistant with NLP and give it an artificial personality, ready to tackle real-world tasks and even crack jokes. What you will learn - Get started with robotics and AI essentials - Understand path planning, decision trees, and search algorithms to enhance your robot - Explore object recognition using neural networks and supervised learning techniques - Employ genetic algorithms to enable your robot arm to manipulate objects - Teach your robot to listen using Natural Language Processing through an expert system - Program your robot in how to avoid obstacles and retrieve objects with machine learning and computer vision - Apply simulation techniques to give your robot an artificial personality Who this book is for This book is for practicing robotics engineers and enthusiasts aiming to advance their skills by applying AI and ML techniques. Students and researchers looking for practical guidance for solving specific problems or approaching a difficult robot design will find this book insightful. Proficiency in Python programming, familiarity with electronics and wiring, single board computers, Linux-based command-line interface (CLI), and knowledge of AI/ML concepts are required to get started with this book. Table of Contents - The Foundation of Robotics and Artificial Intelligence - Setting Up Your Robot - Conceptualizing the Practical Robot Design Process - Recognizing Objects Using Neural Networks and Supervised Learning - Picking Up and Putting Away Toys using Reinforcement Learning and Genetic Algorithms - Teaching a Robot to Listen - Teaching the Robot to Navigate and Avoid Stairs - Putting Things Away - Giving the Robot an Artificial Personality - Conclusions and Reflections - Q and A - Apendix...