Public research sourceMITRuss Tedrake / Underactuated Robotics
MIT: How Unstable Robots Regain Balance
First understand what MIT researchers are trying to learn through Russ Tedrake / Underactuated Robotics, why the question matters, how they test it, and what the result cannot prove. Make an unstable simulated pole regain balance, then compare what changes at different starting angles. The student then completes A robot-balance control app for selecting correction methods and testing recovery from different starting positions. For a college application or interview, the student separates the source research from their feature, interface, tests, failures, and revisions. Available online or in person in Apgujeong, in one-to-one or small-group formats.
University and lab names show where each public project came from. CIT independently designed these courses; they are not official university courses, partnerships, or endorsements.
8guided sessions
6-12 hoursto the first small project
Intermediaterecommended level
Not requiredphysical robot
Primary routes
Choose the student's primary AI education and portfolio route
CIT keeps the international-school route first, followed by the separate science and gifted-school route.
CIT lessons can run online across Korea and overseas or in person in Apgujeong. The student owns the question, code, tests and explanation; classes do not guarantee admission, selection or awards, and online delivery never changes an institution's submission rules.
Can an unstable robot with limited motors automatically regain its balance?
Experiment with how a pendulum or a pole balanced on a moving cart automatically regains balance. Difficult equations are explained with motion graphs.
Students first use a small working example to understand the researchers' question, method, and evidence. A controlled change helps identify what the student's extension must solve. The student then implements a useful feature, connects an operator interface, and tests the integrated application in normal, boundary, and failure cases.
What will the student complete?
A robot-balance control app for selecting correction methods and testing recovery from different starting positions
The final package includes runnable instructions, the feature and interface design, normal and failure tests, one documented revision, and a three-minute explanation in the student's own words.
Feature
A feature that tests gentle, medium, and strong automatic correction at a chosen starting angle and reports whether balance returns
Operator interface
A balance-control screen for choosing starting angle and correction strength while viewing position, speed, and motor-force graphs
Integrated result
A robot-balance control app for selecting correction methods and testing recovery from different starting positions
Four ideas explained in this course
01physics rules that shape motion
02motion graphs over time
03automatic correction from error
04calculating the force needed for balance
Eight introductory sessions
Understand the research, then build and test a working robotics application
The 20 courses are eight-session CIT studios in which students understand a public university or lab project, confirm a working example, and then turn it into a small robotics application with a useful feature and an operator interface. Selected courses add an optional LLM explanation tool that can read run records but cannot control the robot. RoboMaster has 28 sessions, and implementation scope is adjusted to each student's experience and computer access.
Understand the source
01
Run MIT's simulated unstable pole
02
Understand position, speed, and motion rules
Measure and compare
03
Read changing motion on a graph
04
Compare fixed commands with automatic correction
Build a feature
05
Change only the starting angle
06
Implement the student-owned feature: A feature that tests gentle, medium, and strong automatic correction at a chosen starting angle and reports whether balance returns
Integrate and demonstrate
07
Build the operator interface: A balance-control screen for choosing starting angle and correction strength while viewing position, speed, and motor-force graphs
08
Integrate, test, and demonstrate: A robot-balance control app for selecting correction methods and testing recovery from different starting positions
Public project used in class
See the exact version CIT reviewed
Public projects can change over time. To keep the class example consistent, CIT uses version 26e9a5bbb5b9 of RussTedrake/underactuated. CIT checked it on 2026-08-14; it was created on 2026-05-25. Usage-rights note: No top-level license file found at review; follow file-level and site terms.
licence No top-level license file found at review; follow file-level and site terms
text files 331
The student lowers the motor force on a swinging robot and sees how its way of balancing changes. In class the project is separated into five boxes (input, memory, process, output, control). The lesson opens one of them, changes one value, and leaves the rest closed.
InputWhat comes in?
The model that writes the links and joints, and the pose the swing starts from
Memoryopened hereWhat persists?
The angle and the angular velocity: the present state written as a few numbers
ProcessWhat transforms?
The control law that reads those numbers and decides how much the motor gets
OutputWhat leaves, and who uses it?
The path the state traces over time, and whether the target pose was held
ControlWhat decides when anything runs?
The switch that decides whether the swing-up controller or the balancing one is in charge
The files the lesson opens, by name. The course is not a walk through the repository; it opens a chosen few and says which.
One value moves and everything else stays. The right-hand column is the prediction written before the run, not a result; the work is reconciling the two.
The universities and labs named here made the open projects this course reads. CIT designed the course independently; it is not an official, affiliated, or endorsed course.
Clear answers about what students do, what they need, and where the project came from.
Is MIT: How Unstable Robots Regain Balance an official course from MIT, Russ Tedrake's Underactuated Robotics?
University and lab names show where each public project came from. CIT independently designed these courses; they are not official university courses, partnerships, or endorsements.
Is hardware required?
Not required. The course starts with a robot on the computer or a saved recording of a completed run. Computer guidance: CPU suitable.
What background should a student have?
Recommended level: Intermediate. Students should be able to follow a guided Python example, test one controlled change, and then build and explain a small feature and interface.
What will the student make?
The completed project is A robot-balance control app for selecting correction methods and testing recovery from different starting positions. The student implements A feature that tests gentle, medium, and strong automatic correction at a chosen starting angle and reports whether balance returns and A balance-control screen for choosing starting angle and correction strength while viewing position, speed, and motor-force graphs.
How can the student use this project in a college application?
Explain the source research question, method, evidence, and limits first. Then separate the student's own feature and interface decisions, normal and failure tests, revisions, and next question. The source institution's name does not imply affiliation or guarantee admission.
Which project version does the course use?
CIT reviewed version 26e9a5bbb5b9 of RussTedrake/underactuated on 2026-08-14. That version was created on 2026-05-25. We keep this version during class so the example does not change unexpectedly, and we check the setup again before teaching.
Can MIT: How Unstable Robots Regain Balance be taken online or in person, one-to-one or in a small group?
Yes. This course is offered online and in person at CIT in Apgujeong, Gangnam-gu, Seoul, with one-to-one and small-group options. Placement and current availability are confirmed after a readiness consultation.
Is this a good first project for this student?
Before placement, we check the student's coding and math experience, available computer, interests, and ability to explain what happened.
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