RoboMaster: Responding to Voice, Gesture, and Vision Safely
Command a robot with voice and gestures, then make it stop automatically when its camera or distance sensor finds danger. First understand the robotics question, the method used to test it, and the result's limits. The student then completes A RoboMaster rescue-mission console that combines multiple inputs while enforcing student approval and automatic stopping. For a college application or interview, the student separates the source idea from their feature, interface, tests, failures, and revisions. Available online or in person in Apgujeong, in one-to-one or small-group formats.
CIT independently designed this course from public source material. The DJI name only identifies the robot platform; it does not mean DJI is a partner or sponsor.
28guided sessions
8-20 hoursto the first small project
Middle school and above, readiness-based routesrecommended level
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 a robot respond to voice, gestures, camera images, and distance sensors while always stopping safely?
Combine voice, gesture, camera, and distance signals to move a robot. Build safeguards that stop it when communication fails or sensor data arrives late.
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 RoboMaster rescue-mission console that combines multiple inputs while enforcing student approval and automatic stopping
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 combines voice, gesture, camera, and distance-sensor requests into one format and stops before any other command when risk appears
Operator interface
A rescue-mission console showing current input, student approval, robot state, issued command, and automatic-stop reason
Optional LLM boundary
Optional: an LLM turns a spoken request into a draft of allowed mission steps. It cannot bypass student approval, sensor checks, or the emergency stop.
Integrated result
A RoboMaster rescue-mission console that combines multiple inputs while enforcing student approval and automatic stopping
Four ideas explained in this course
01voice, gesture, and camera signals
02the roles of three computers
03combining several sensors
04stopping automatically in danger
28 sessions summarized in 8 steps
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
Review official setup and the public project
02
Set stop-first rules across three computers
Measure and compare
03
Put voice, gesture, and camera signals in one format
04
Use a camera to find people, objects, and signs
Build a feature
05
Send commands safely among three computers
06
Implement the student-owned feature: A feature that combines voice, gesture, camera, and distance-sensor requests into one format and stops before any other command when risk appears
Integrate and demonstrate
07
Build the operator interface: A rescue-mission console showing current input, student approval, robot state, issued command, and automatic-stop reason. Add the bounded assistant: Optional: an LLM turns a spoken request into a draft of allowed mission steps. It cannot bypass student approval, sensor checks, or the emergency stop.
08
Integrate, test, and demonstrate: A RoboMaster rescue-mission console that combines multiple inputs while enforcing student approval and automatic stopping
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 bd7188777f5b of jojungwhan/robomaster-yolo-ai. CIT checked it on 2026-08-14; it was created on 2026-08-07. Usage-rights note: No license file in the reviewed version; local study only until rights are confirmed.
Clear answers about what students do, what they need, and where the project came from.
Is RoboMaster: Responding to Voice, Gesture, and Vision Safely an official course from CIT course based on DJI RoboMaster and an independent public repository?
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?
RoboMaster optional, dry-run available. The course starts with a robot on the computer or a saved recording of a completed run. Computer guidance: Windows PC; saved practice recordings are provided.
What background should a student have?
Recommended level: Middle school and above, readiness-based routes. 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 RoboMaster rescue-mission console that combines multiple inputs while enforcing student approval and automatic stopping. The student implements A feature that combines voice, gesture, camera, and distance-sensor requests into one format and stops before any other command when risk appears and A rescue-mission console showing current input, student approval, robot state, issued command, and automatic-stop reason. Optional: an LLM turns a spoken request into a draft of allowed mission steps. It cannot bypass student approval, sensor checks, or the emergency stop.
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 bd7188777f5b of jojungwhan/robomaster-yolo-ai on 2026-08-14. That version was created on 2026-08-07. We keep this version during class so the example does not change unexpectedly, and we check the setup again before teaching.
Can RoboMaster: Responding to Voice, Gesture, and Vision Safely 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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