Public research sourceGeorgia TechFrank Dellaert / Seth Hutchinson
Georgia Tech: Robot Sensors and Position Finding
First understand what Georgia Tech researchers are trying to learn through Frank Dellaert / Seth Hutchinson, why the question matters, how they test it, and what the result cannot prove. Compare a robot's position estimate with accurate and inaccurate sensors, then show the difference on a graph. The student then completes A robot-localization tool for changing sensor combinations and error while viewing the estimate and its uncertainty. 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
3-6 hoursto the first small project
Beginnerrecommended 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.
How well can a robot find its position when its sensor readings become less accurate?
Run an example in which a robot uses a map and sensor readings to find its position. Graph how its estimate changes as sensor error grows.
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-localization tool for changing sensor combinations and error while viewing the estimate and its uncertainty
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 adds, removes, or adds error to a sensor and recalculates how much the robot's position estimate changes
Operator interface
A localization screen with a sensor-error slider and a map showing the estimated position and uncertainty area
Integrated result
A robot-localization tool for changing sensor combinations and error while viewing the estimate and its uncertainty
Four ideas explained in this course
01describing position with numbers
02comparing possibilities
03errors in sensor readings
04the robot's position estimate
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
Open the web notebook and review usage limits
02
Describe screen positions with numbers
Measure and compare
03
Calculate the direction a robot moves
04
Understand landmarks and sensor information
Build a feature
05
Change only the sensor error
06
Implement the student-owned feature: A feature that adds, removes, or adds error to a sensor and recalculates how much the robot's position estimate changes
Integrate and demonstrate
07
Build the operator interface: A localization screen with a sensor-error slider and a map showing the estimated position and uncertainty area
08
Integrate, test, and demonstrate: A robot-localization tool for changing sensor combinations and error while viewing the estimate and its uncertainty
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 49315552e7f6 of gtbook/robotics. CIT checked it on 2026-08-14; it was created on 2026-01-10. Usage-rights note: BSD-3-Clause for repository code; book prose has separate terms.
licence BSD-3-Clause for repository code; book prose has separate terms
text files 94
The student raises the sensor error and watches how far the robot loses track of itself. 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 sensor reading each notebook takes in, and the action the robot just made
Memoryopened hereWhat persists?
The probability spread across every place the robot could be
ProcessWhat transforms?
The computation that redistributes those probabilities when a new reading arrives
OutputWhat leaves, and who uses it?
The corrected probabilities, and the next action chosen from them
ControlWhat decides when anything runs?
The order that alternates acting and observing
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 Georgia Tech: Robot Sensors and Position Finding an official course from Georgia Tech based, by Frank Dellaert and Seth Hutchinson?
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: Binder or a standard notebook.
What background should a student have?
Recommended level: Beginner. 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-localization tool for changing sensor combinations and error while viewing the estimate and its uncertainty. The student implements A feature that adds, removes, or adds error to a sensor and recalculates how much the robot's position estimate changes and A localization screen with a sensor-error slider and a map showing the estimated position and uncertainty area.
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 49315552e7f6 of gtbook/robotics on 2026-08-14. That version was created on 2026-01-10. We keep this version during class so the example does not change unexpectedly, and we check the setup again before teaching.
Can Georgia Tech: Robot Sensors and Position Finding 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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