Artificial Intelligence for Robotics
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Artificial Intelligence for Robotics
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What you'll learn
Apply AI and ML techniques to enhance robot perception and decision-making
Implement object recognition and navigation strategies using neural networks and algorithms
Integrate natural language processing to enable voice and personality features in robots
Skills you'll gain
Tools you'll learn
Details to know
March 2026
11 assignments
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There are 11 modules in this course
This course dives deep into the integration of artificial intelligence and machine learning within robotics. You will learn to build intelligent robots capable of performing real-world tasks using ROS 2, Python, OpenCV, and advanced AI/ML techniques. By focusing on neural networks, computer vision, and natural language processing, this course will help you enhance robot functionality for complex tasks.
Throughout the course, you will improve your skills in applying AI and ML techniques, implementing object recognition systems, and navigating robots. The content is designed for hands-on learning, allowing you to work on practical problems while developing a real-world understanding of intelligent robotics systems. What sets this course apart is its unique combination of theory and practical application. The course integrates state-of-the-art AI/ML concepts into the design and development of robotics projects, equipping you with the tools to work on intelligent robot systems. The hands-on approach makes the theoretical knowledge more accessible and applicable in real-life scenarios. This course is perfect for robotics engineers, AI/ML enthusiasts, and students with a background in Python and electronics. If you're looking to create smarter, more capable robots, this course will help you take your skills to the next level.
In this section, we explore integrating AI into robotics, focusing on decision-making, learning, and autonomy. Key concepts include neural networks, reinforcement learning, and autonomous behavior design.
What's included
2 videos9 readings1 assignment
2 videos•Total 2 minutes
- Course Overview•1 minute
- The Foundation of Robotics and Artificial Intelligence - Overview Video•1 minute
9 readings•Total 90 minutes
- Introduction•10 minutes
- Are Recent Developments in AI Anything New•10 minutes
- The Basics of Robotics•10 minutes
- When Do You Need AI for Your Robot•5 minutes
- Introducing the Robot and Our Development Environment•10 minutes
- Software Components (ROS, Python, and Linux)•10 minutes
- Using Control Loops•10 minutes
- Types of Control Loops•5 minutes
- Running a Control Loop•20 minutes
1 assignment•Total 10 minutes
- Exploring the Foundations of Robotics and AI•10 minutes
In this section, we explore robot anatomy, subsumption architecture, and ROS 2 setup to enable practical robotic system development through structured hardware and software configuration.
What's included
1 video5 readings1 assignment
1 video•Total 1 minute
- Setting Up Your Robot - Overview Video•1 minute
5 readings•Total 60 minutes
- Introduction•20 minutes
- Introducing Subsumption Architecture•10 minutes
- A Brief Introduction to ROS•10 minutes
- Hardware and Software Setup•10 minutes
- Understanding How ROS Works•10 minutes
1 assignment•Total 10 minutes
- Robot Software Development Essentials•10 minutes
In this section, we explore systems engineering principles for robot design, focusing on use cases, storyboards, and hardware/software requirements to guide practical robotic task development.
What's included
1 video5 readings1 assignment
1 video•Total 1 minute
- Conceptualizing the Practical Robot Design Process - Overview Video•1 minute
5 readings•Total 85 minutes
- Introduction•20 minutes
- Our Robot's Task•5 minutes
- What Is Our Robot to Do•10 minutes
- Using Storyboards•30 minutes
- Project Goals•20 minutes
1 assignment•Total 10 minutes
- Robot Design Fundamentals•10 minutes
In this section, we explore using convolutional neural networks (CNNs) and YOLOv8 for object recognition, focusing on image processing, supervised learning, and real-world applications in robotics and AI.
What's included
1 video5 readings1 assignment
1 video•Total 1 minute
- Recognizing Objects Using Neural Networks and Supervised Learning - Overview Video•1 minute
5 readings•Total 70 minutes
- Introduction•20 minutes
- Artificial Neurons•10 minutes
- Using YOLOv8 An Object Recognition Model•10 minutes
- Understanding How to Train Our Toy Detector•20 minutes
- Building the Toy Detector•10 minutes
1 assignment•Total 10 minutes
- Fundamentals of Object Recognition with Neural Networks•10 minutes
In this section, we explore training robots using reinforcement learning and genetic algorithms. Key concepts include Q-learning for grasping and GA-based path planning for autonomous manipulation.
What's included
1 video8 readings1 assignment
1 video•Total 1 minute
- Picking Up and Putting Away Toys Using Reinforcement Learning and Genetic Algorithms - Overview Video•1 minute
8 readings•Total 125 minutes
- Introduction•10 minutes
- Designing the Software•10 minutes
- Setting Up the Solution•5 minutes
- How Do We Pick Actions•5 minutes
- Creating the Interface to the Arm•30 minutes
- Introducing Q-Learning for Grasping Objects•30 minutes
- Introducing GAs•5 minutes
- Building a GA Process•30 minutes
1 assignment•Total 10 minutes
- Learning from Feedback and Evolution in Robotics•10 minutes
In this section, we explore robot speech recognition using NLP, STT, and TTS, and implement command processing with Mycroft to enhance natural language understanding and response generation.
What's included
1 video7 readings1 assignment
1 video•Total 1 minute
- Teaching a Robot to Listen - Overview Video•1 minute
7 readings•Total 85 minutes
- Introduction•10 minutes
- Listening for the Wake Word•10 minutes
- Clarifying the Intent•10 minutes
- Adding Skills•5 minutes
- Cleaning up the toys•20 minutes
- Telling Jokes•20 minutes
- Receiving Jokes•10 minutes
1 assignment•Total 10 minutes
- Robot Listening and Speech Recognition Fundamentals•10 minutes
In this section, we explore robot navigation strategies without SLAM, focusing on AI-driven obstacle avoidance and sensor-based movement for efficient task execution.
What's included
1 video7 readings1 assignment
1 video•Total 1 minute
- Teaching the Robot to Navigate and Avoid Stairs - Overview Video•1 minute
7 readings•Total 60 minutes
- Introduction•10 minutes
- Understanding the SLAM Methodology•10 minutes
- Exploring Alternative Navigation Techniques•10 minutes
- Implementing Neural Networks•5 minutes
- Processing the image•5 minutes
- Training the Neural Network for Navigation•10 minutes
- CNN Robot Control Implementation•10 minutes
1 assignment•Total 10 minutes
- Understanding Robot Navigation and Sensor Use•10 minutes
In this section, we explore AI decision-making tools like decision trees, path planning, and expert systems for robotics.
What's included
1 video8 readings1 assignment
1 video•Total 1 minute
- Putting Things Away - Overview Video•1 minute
8 readings•Total 105 minutes
- Introduction•10 minutes
- What Do We Mean by Pruning?•5 minutes
- Creating Self-Classifying Decision Trees•30 minutes
- Understanding Entropy•20 minutes
- Random Forests•10 minutes
- Developing a Map Based on Our Knowledge•10 minutes
- Introducing the A* Algorithm•10 minutes
- Introducing the D (D-star or Dynamic A) Algorithm•10 minutes
1 assignment•Total 10 minutes
- Navigating Algorithms and Data Structures•10 minutes
In this section, we explore simulating artificial personality in robots using finite state machines and AI. Key concepts include behavior modeling and emotion simulation for practical robotic applications.
What's included
1 video10 readings1 assignment
1 video•Total 1 minute
- Giving the Robot an Artificial Personality - Overview Video•1 minute
10 readings•Total 80 minutes
- Introduction•10 minutes
- A Brief Introduction to the (Obsolete) Turing Test, Chatbots, and Generative AI•5 minutes
- The Art and Science of Simulation•10 minutes
- An Emotion State Machine•5 minutes
- Playing the Emotion Game•5 minutes
- Creating a Model of Human Behavior•5 minutes
- Constructing a Personality•10 minutes
- Adding Context•10 minutes
- Developing the Robot Emotion Engine•10 minutes
- Creating Human Information Storage•10 minutes
1 assignment•Total 10 minutes
- Robot Emotion and Artificial Personality•10 minutes
In this section, we examine when to stop in AI development, explore robotics career paths, and assess AI risks to support informed decision-making in real-world applications.
What's included
1 video6 readings1 assignment
1 video•Total 1 minute
- Conclusions and Reflections - Overview Video•1 minute
6 readings•Total 40 minutes
- Introduction•5 minutes
- Careers in Robotics•5 minutes
- Exploring the Current State of AI•5 minutes
- Is AI Phobia Reasonable?•5 minutes
- Comparing the Needs of Humans and AI•10 minutes
- Understanding Risk in AI•10 minutes
1 assignment•Total 10 minutes
- Reflections on Technology and Human Interaction•10 minutes
In this section, we will explore the foundational elements of robot communication and system design.
What's included
3 readings1 assignment
3 readings•Total 30 minutes
- Introduction•10 minutes
- Software Requirements for the Robot•10 minutes
- Introducing the Hardware for the Robot•10 minutes
1 assignment•Total 10 minutes
- ROS and Robotics Fundamentals•10 minutes
Instructor
Explore more from Software Development
- Status: Free TrialU
University of Michigan
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- Status: PreviewC
Coursera
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- Status: Free TrialL
L&T EduTech
Course
- Status: Free Trial
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