Applying AI to Robotics

Artificial Intelligence    |    Expert
  • 17 videos | 57m
  • Includes Assessment
  • Earns a Badge
Rating 4.4 of 312 users Rating 4.4 of 312 users (312)
Robots can utilize machine learning, deep learning, reinforcement learning, as well as probabilistic techniques to achieve intelligent behavior. This application of AI to robotic systems is found in the automotive, healthcare, logistics, and military industries. With increasing computing power and sophistication in small robots, more industry use cases are likely to emerge, making AI development for robotics a useful AI developer skill. In this course, you'll explore the main concepts, frameworks, and approaches needed to work with robotics and apply AI to robots. You'll examine how AI and robotics are used across multiple industries. You'll learn how to work with commonly used algorithms and strategies to develop simple AI systems that improve the performance of robots. Finally, you'll learn how to control a robot in a simulated environment using deep Q-networks.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline a brief history of the robotics industry
    Identify the role ai plays in the robotics industry
    Describe the concept of a cobot and list multiple cobot use cases
    List possible applications and use cases of ai in the robotics industry
    Specify how ai and robotics are used in the automotive industry
    Specify how ai and robotics are used in the healthcare industry
    Specify how ai and robotics are used in the manufacturing industry
    Specify how ai and robotics are used for warehouse automation and logistics
  • Specify how ai and robotics are applied in the military
    List open source robotics frameworks and identify the context of their application
    Define the role of reinforcement learning in robotics
    Give examples of how cognitive and deep learning models are used in the robotics industry
    Use common ai tools to improve the navigation of robots across surfaces
    Work with deep q-networks to control a robot in a simulated environment
    Configure a robotics ai pipeline using the ros framework in jupyter notebooks
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 45s
  • 3m 56s
    In this video, you will learn how to outline a brief history of the robotics industry. FREE ACCESS
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    3.  AI in Robotics
    3m 51s
    In this video, find out how to identify the role that AI plays in the robotics industry. FREE ACCESS
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    4.  Collaborative Robots: Cobots
    5m 15s
    Upon completion of this video, you will be able to describe the concept of a cobot and list multiple cobot use cases. FREE ACCESS
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    5.  AI and Robotics: Applications
    1m 26s
    Upon completion of this video, you will be able to list possible applications and use cases of AI in the robotics industry. FREE ACCESS
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    6.  AI and Robotics in the Automotive Industry
    3m 24s
    Upon completion of this video, you will be able to specify how AI and robotics are used in the automotive industry. FREE ACCESS
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    7.  AI and Robotics in Healthcare
    3m 9s
    Upon completion of this video, you will be able to specify how AI and robotics are used in healthcare. FREE ACCESS
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    8.  AI and Robotics in Manufacturing
    2m 25s
    Upon completion of this video, you will be able to specify how artificial intelligence and robotics are used in the manufacturing industry. FREE ACCESS
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    9.  AI and Robotics in Logistics
    2m 20s
    Upon completion of this video, you will be able to specify how AI and robotics are used for warehouse automation and logistics. FREE ACCESS
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    10.  AI and Robotics in the Military
    3m 9s
    Upon completion of this video, you will be able to specify how AI and robotics are used in the military. FREE ACCESS
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    11.  Open Source Robotics
    3m 6s
    Upon completion of this video, you will be able to list open source robotics frameworks and identify the context of their application. FREE ACCESS
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    12.  Reinforcement Learning in Robotics
    4m 46s
    Find out how to define the role of reinforcement learning in robotics. FREE ACCESS
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    13.  Cognitive and Deep Learning Models in Robotics
    3m 8s
    In this video, you will give examples of how cognitive and deep learning models are used in the robotics industry. FREE ACCESS
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    14.  Predict Floor Surfaces Using a Robot’s Sensor data
    4m 1s
    In this video, you will learn how to use common AI tools to improve the navigation of robots across surfaces. FREE ACCESS
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    15.  Deep Reinforcement Learning for Robotics
    4m 38s
    During this video, you will learn how to work with deep Q-networks to control a robot in a simulated environment. FREE ACCESS
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    16.  ROS and Jupyter Notebooks
    5m 57s
    During this video, you will learn how to configure a robotics AI pipeline using the ROS framework in Jupyter Notebooks. FREE ACCESS
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    17.  Course Summary
    43s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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