2023 | English | 1098134259 | EPUB | 72 pages | 6 MB

Machine learning is the future of robotics, whether for self-driving vehicles, industrial manufacturing, or consumer products. Driven by widespread advances in research, industrial deployment of huge neural nets, and end-to-end robotics tasks, the science and practice of robotics is on the cusp of disruption from data-driven approaches such as deep learning. If you're a software or machine learning engineer looking to get into robotics, or a robotics engineer looking to deploy machine learning in your projects, this is your book.
You'll learn how to apply deep learning methods to robotics and how to approach robotics core technologies—perception, prediction, localization, and decision-making—from a deep learning perspective. This guide discusses state-of-the-art deep learning algorithms relevant to each core technology, how to use them for real-world robotics and includes relevant code samples to demonstrate how these algorithms can be applied.
You'll learn how to
Apply state-of-the-art techniques in AI to robotics systems
Learn factors driving decision-making in technical design for several robotics applications
Understand how ML and robotics are useful for research or organizational purposes
Learn the technology behind designing and deploying modern robotics: sensing, perception, training, and control
Design robotic systems for real-world applications: self-driving, prosthetics, and industrial automation

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