Robotics is a branch of engineering and science that deals with other disciplines such as mathematical engineering, electrical engineering, and computer science. Since the usage of robots has increased through the years, knowing the core technologies in creating robots can be beneficial.
This [course_title] is created for you to learn the natural dynamics of robotics. You will learn from this course how to actually control different mechanical systems of robots.
Assessment
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
Certification
Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49.
Having an Official Edukite Certification is a great way to celebrate and share your success. You can:
- Add the certificate to your CV or resume and brighten up your career
- Show it to prove your success
Course Credit: MIT
Course Curriculum
| Module: 1 | |||
| Lecture 1: Introduction | 01:14:00 | ||
| Lecture 2: The Simple Pendulum | 01:19:00 | ||
| Lecture 3: Optimal Control of the Double Integrator | 01:17:00 | ||
| Lecture 4: Optimal Control of the Double Integrator (cont.) | 01:25:00 | ||
| Lecture 5: Numerical Optimal Control (Dynamic Programming) | 01:13:00 | ||
| Lecture 6: Acrobot and Cart-pole | 01:20:00 | ||
| Module: 2 | |||
| Lecture 7: Swing-up Control of Acrobot and Cart-pole Systems | 01:06:00 | ||
| Lecture 8: Dynamic Programming (DP) and Policy Search | 01:14:00 | ||
| Lecture 9: Trajectory Optimization | 01:09:00 | ||
| Lecture 10: Trajectory Stabilization and Iterative Linear Quadratic Regulator | 01:20:00 | ||
| Lecture 11: Walking | 01:16:00 | ||
| Lecture 12: Walking (cont.) | 01:12:00 | ||
| Module: 3 | |||
| Lecture 13: Running | 00:58:00 | ||
| Lecture 14: Feasible Motion Planning | 01:14:00 | ||
| Lecture 15: Global Policies from Local Policies | 01:19:00 | ||
| Lecture 16: Introducing Stochastic Optimal Control | 01:24:00 | ||
| Lecture 17: Stochastic Gradient Descent | 01:17:00 | ||
| Module: 4 | |||
| Lecture 18: Stochastic Gradient Descent 2 | 01:19:00 | ||
| Lecture 19: Temporal Difference Learning | 01:20:00 | ||
| Lecture 20: Temporal Difference Learning with Function Approximation | 01:18:00 | ||
| Lecture 21: Policy Improvement | 01:16:00 | ||
| Lecture 22: Actor-critic Methods | 01:11:00 | ||
| Lecture 23: Case Studies in Computational Underactuated Control | 01:02:00 | ||
| Assessment | |||
| Submit Your Assignment | 00:00:00 | ||
| Certification | 00:00:00 | ||
Course Reviews
No Reviews found for this course.
Related Courses
