Applying AI to Robotics
Artificial Intelligence
| Expert
- 17 videos | 57m
- Includes Assessment
- Earns a Badge
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
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discover the key concepts covered in this courseoutline a brief history of the robotics industryidentify the role AI plays in the robotics industrydescribe the concept of a cobot and list multiple cobot use caseslist possible applications and use cases of AI in the robotics industryspecify how AI and robotics are used in the automotive industryspecify how AI and robotics are used in the healthcare industryspecify how AI and robotics are used in the manufacturing industryspecify how AI and robotics are used for warehouse automation and logistics
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specify how AI and robotics are applied in the militarylist open source robotics frameworks and identify the context of their applicationdefine the role of reinforcement learning in roboticsgive examples of how cognitive and deep learning models are used in the robotics industryuse common AI tools to improve the navigation of robots across surfaceswork with deep Q-networks to control a robot in a simulated environmentconfigure a robotics AI pipeline using the ROS framework in Jupyter Notebookssummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 45sUP NEXT
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2.A History of Robotics3m 56s
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3.AI in Robotics3m 51s
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4.Collaborative Robots: Cobots5m 15s
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5.AI and Robotics: Applications1m 26s
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6.AI and Robotics in the Automotive Industry3m 24s
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7.AI and Robotics in Healthcare3m 9s
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8.AI and Robotics in Manufacturing2m 25s
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9.AI and Robotics in Logistics2m 20s
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10.AI and Robotics in the Military3m 9s
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11.Open Source Robotics3m 6s
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12.Reinforcement Learning in Robotics4m 46s
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13.Cognitive and Deep Learning Models in Robotics3m 8s
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14.Predict Floor Surfaces Using a Robot’s Sensor data4m 1s
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15.Deep Reinforcement Learning for Robotics4m 38s
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16.ROS and Jupyter Notebooks5m 57s
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17.Course Summary43s
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