Public research sourcePrinceton / Toyota Research InstituteIROM / AdaptSim
Princeton AdaptSim: Closing the Simulation-to-Reality Gap
First understand what Princeton / Toyota Research Institute researchers are trying to learn through IROM / AdaptSim, why the question matters, how they test it, and what the result cannot prove. Give a simulated robot deliberately incorrect weight or friction, then adjust it until its result is closer to the real example. The student then completes A robot-calibration tool that finds physics settings that reduce the simulation-to-reality gap and saves a settings profile. 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
12-24 hoursto the first small project
Advancedrecommended 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.
Which physics setting should we adjust first to make a simulated robot behave more like the real one?
A simulated robot behaves differently when its weight or friction does not match reality. Test which adjustment reduces that difference.
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-calibration tool that finds physics settings that reduce the simulation-to-reality gap and saves a settings profile
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 uses the result gap between two simulated robots to narrow and save candidate physics adjustments
Operator interface
A calibration screen with an error heatmap across mass and friction candidates and a before-and-after accuracy comparison
Integrated result
A robot-calibration tool that finds physics settings that reduce the simulation-to-reality gap and saves a settings profile
Four ideas explained in this course
01differences between simulation and reality
02weight and friction settings
03adjusting again from results
04task accuracy
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 the prepared simulated environment
02
Understand the two robot models being compared
Measure and compare
03
Choose a result and setting to compare
04
Measure the difference before adjustment
Build a feature
05
Change only weight or friction
06
Implement the student-owned feature: A feature that uses the result gap between two simulated robots to narrow and save candidate physics adjustments
Integrate and demonstrate
07
Build the operator interface: A calibration screen with an error heatmap across mass and friction candidates and a before-and-after accuracy comparison
08
Integrate, test, and demonstrate: A robot-calibration tool that finds physics settings that reduce the simulation-to-reality gap and saves a settings profile
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 9cf80fb42687 of irom-princeton/AdaptSim. CIT checked it on 2026-08-14; it was created on 2024-03-27. Usage-rights note: MIT.
The student runs experiments that close the gap between a simulated robot and a real result, one value at a time. 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 result of the real task being matched, and the simulated setup of the same task
Memoryopened hereWhat persists?
The candidate range of the physics values being tuned, and the record of what has been tried
ProcessWhat transforms?
The part that reads the gap between simulated and target results and picks the next physics values to try
OutputWhat leaves, and who uses it?
The tuned physics values and a summary of the task success rate they produce
ControlWhat decides when anything runs?
The trainer that decides how many times to repeat simulate, compare and update
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 Princeton AdaptSim: Closing the Simulation-to-Reality Gap an official course from Princeton IROM with Toyota Research Institute?
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: Check Ubuntu 20.04 and custom Drake dependencies.
What background should a student have?
Recommended level: Advanced. 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-calibration tool that finds physics settings that reduce the simulation-to-reality gap and saves a settings profile. The student implements A feature that uses the result gap between two simulated robots to narrow and save candidate physics adjustments and A calibration screen with an error heatmap across mass and friction candidates and a before-and-after accuracy comparison.
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 9cf80fb42687 of irom-princeton/AdaptSim on 2026-08-14. That version was created on 2024-03-27. We keep this version during class so the example does not change unexpectedly, and we check the setup again before teaching.
Can Princeton AdaptSim: Closing the Simulation-to-Reality Gap 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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