Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks

AI for Robotics is a comprehensive and engaging guide that empowers readers with the essential skills to create their own robots using ML techniques. The book covers a wide range of topics, including computer vision, object recognition, genetic algorithms, and reinforcement learning, providing a solid foundation for both beginners and experienced roboticists.One of the strengths of this book is its practical approach. Govers, who, for anyone in the field knows, is an established pioneer in robotics and AI, provides detailed instructions and clear explanations, making it easy for readers to follow along and build their own robots. The book also includes numerous illustrations and code examples, which further enhance the learning experience.Another highlight of the book is its holistic framing, with content at the intersection of coding (modern frameworks with Python), ML techniques, and decision-making theory. The author recognizes the importance of AI in modern robotics, but doesn't shy away from a more multi-disciplinary perspective. This combination make the lessons land in a deeper way. Few books out there that I've seen blend all the various topics of robotics together in such a seamless way.Overall, this is an excellent resource for anyone interested in building their own robots (including beginners). The book's comprehensive coverage, practical approach, and focus on AI make it a valuable addition to the robotics literature. I highly recommend it to anyone who wants to learn how to build and program their own robots.

I had high hopes and was really looking forward to working through this book. The theory and concept are well written and easy to understand. However, actually building this project is a huge challenge for even the intermediate or advanced hobbyist. GitHub repo is outdated and not (yet) matching what the book is asking you to do. Same goes for the parts list or missing wiring diagrams. I've already spent around $500 trying to get this going but struggling just to get basic robot building done, let alone any coding or testing. I have a background in electrical engineering and machine learning so was hoping this book/project would provide a good base from which to continue my learning and experiments with AI driven approaches to robotics. Be warned, there's a lot of setup required first and a steep learning curve for anyone new to this. If the code/schedmatics improve I'll consider revising my review.

The book takes on the task of introducing AI techniques for programming a mobile robot. The chapters progressively cover AI-generated perception, navigation, and human-computer interaction tasks. This is distinctly different than the usual command and control paradigm used by most introductory robotics guides. The concepts are covered in a thorough and compelling manner with the intermediate student or hobbyist in mind. However, the reader should be aware that the example code is not consistently in ROS2. Some code is transferred from the first edition of the book and is in ROS1 and Python 2. The code will require a rewrite to ROS2. Something the intermediate student should be able to accomplish. Although individual tasks are complete as written, some additional code will need to be written to produce a fully functional robot. These deficiencies could be easily corrected with some additional example code on the GitHub repository.

Good resource for anyone diving into the realms of robotics and artificial intelligence. The book adeptly covers foundational topics like path planning, decision trees, and search algorithms, making complex concepts accessible and applicable. Its exploration of object recognition through neural networks and supervised learning is detailed and practical, perfect for hands-on learners. The sections on employing genetic algorithms to manipulate objects with robot arms are clear and informative, demonstrating the real-world utility of these algorithms. Additionally, the coverage of Natural Language Processing enables robots to understand and process human language, a crucial skill in AI development.Programming guidance for obstacle avoidance and object retrieval using machine learning and computer vision is thorough, with practical examples that are easy to follow. The book also creatively applies simulation techniques to give robots a semblance of personality, making it a fascinating read for those interested in the future of human-robot interactions. Overall, this book is a comprehensive guide that blends theoretical knowledge with practical application, making it a must-read for beginners and intermediate learners in robotics.

If you know enough to buy this book, you don’t need this book. This book is full of concepts and sudo code and you cannot use this book to build a functional robot. For example, it does very little to explain the easiest part, the Arduino that drive the wheels and servos.