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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 Underactuated Robotics Diploma 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

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