Artificial Intelligence (AI) for Robotics Training Course
Robotics is a field within artificial intelligence (AI) that focuses on the development and programming of intelligent and efficient machines.
This instructor-led live training session (either online or in-person) is designed for engineers who want to learn how to program and build robots using fundamental AI techniques.
By the end of this course, participants will be able to:
- Apply filters such as Kalman and particle filters to help a robot identify moving objects within its surroundings.
- Implement search algorithms and motion planning strategies.
- Use PID controls to manage a robot's movement in an environment.
- Utilize SLAM algorithms to allow a robot to map out unfamiliar environments.
Course Format
- Interactive lectures and discussions.
- A variety of exercises and practical practice sessions.
- Hands-on implementation in a live-lab setting.
Customization Options for the Course
- To request a tailored training session, please contact us to make arrangements.
Course Outline
Introduction
Overview of Artificial Intelligence (AI) and Robotics
- Computer-simulated versus physical
- Robotics as a branch of AI
- Applications for AI in robotics
Understanding Localization
- Locating your robot
- Using sensors to assess location and environment
- Probability exercises
Learning About Robot Motion
- Exact and inexact motions
- Sense and move functions
Using Probability Tools
- Bayes’ rule
- Theorem of total probability
Estimating Vehicle State Using Kalman Filter
- Gaussian processes
- Measurement and motion
- Kalman filtering (code, prediction, design, and matrices)
Tracking Your Robotic Car Using Particle Filter
- State space dimension and brief modality
- Robot class, robot world, and robot particles
Exploring Planning and Search Methods
- A* search algorithm
- Motion planning
- Compute cost and optimal path
Programming Your AI Robot
- First search program and expansion grid table
- Dynamic programming
- Computing value and optimal policy
Using PID Control
- Robot motion and path smoothing
- Implementing PID controller
- Parameter optimization
Mapping and Tracking Using SLAM
- Constraints
- Landmarks
- Implementing SLAM
Troubleshooting
Summary and Conclusion
Requirements
- Programming experience
- Basic understanding of computer science and engineering
- Familiarity with probability concepts and linear algebra
Audience
- Engineers
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Testimonials (1)
its knowledge and utilization of AI for Robotics in the Future.
Ryle - PHILIPPINE MILITARY ACADEMY
Course - Artificial Intelligence (AI) for Robotics
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