DJI RoboMaster Tello Talent Educational Drone

As an educational drone developed by DJI Education, RoboMaster TT is committed to lowering the threshold for robot and AI learning, and cultivating students' curiosity and self-confidence during their first contact with science and technology education. To meet this goal, RoboMaster TT embraces open source and has been upgraded on the basis of Tello EDU to facilitate multi-drone control and AI applications through excellent software and hardware scalability. In addition, RoboMaster TT provides complete drone and AI courses and a new competition system to create a new experience in robotics education and fully stimulate students' creativity.

Outstanding Teaching Tool

High-Performance Mechanical Accessories

Powerful Compatibility Features and Abilities

Introduction to Real-World AI Implementation

Teaching Resources

Project-Based Courses

Suitable for Multiple Grade Levels

Aligns with Curriculum Standards

Competition Database

Competition Rules and Operation Plans

Customizable Competition Arrangements

Practical Hands-On Learning

All-New Product. A Small Drone for Big Dreams

As the industry's leading educational drone, RoboMaster TT delivers powerful flight performance with a compact footprint, and uses the cutting-edge DJI flight control algorithms to ensure flight safety and stability. It also has a 5MP HD camera, which delivers smooth and stable flight images. The newly added ESP32 open-source module and other programmable modules are combined with a diverse programming environment to create a professional drone education platform that is convenient for both teachers and students.

Open source, customizable gameplay

Built-in ESP32 open source module: The built-in ESP32 chip provides the Arduino and Micro Python open source programming environments, and supports the Arduino, Micro Python, graphical programming, and multiple offline programming methods. It creates an open-source flying hardware platform for students and teachers that makes it convenient for students to learn embedded programming and develop various applications of aerial robots.

Light flickering with the drone for a better visual experience

Programmable breathing indicator: When using RoboMaster TT with the RGB full-color LED indicator, you can control the light color and flashing frequency through graphical programming, Python, Arduino, and other programming methods. In this way, the programming result is more intuitive, and the flight effect is more impressive.

More innovations displayed on the screen

Programmable dot-matrix screen: RoboMaster TT has an 8×8 red-and-blue LED dot-matrix screen. You can use the graphical programming, Python, Arduino and other programming methods to display various simple patterns, simple animations, or scrolling characters on the dot-matrix screen. On this basis, the dot-matrix screen provides more possibilities for man-drone interaction.

Distance measurement, obstacle avoidance, and intelligent awareness

Integrated ToF infrared ranging sensor: RoboMaster TT is integrated with a single-point ToF sensor, with the maximum measurement distance of 1.2 meters. The drone is suitable for a range of applications in various teaching scenarios, and can implement environmental perception and intelligent obstacle avoidance.

Highly stable dual-band communication

New 5.8-GHz Wi-Fi module: This module supports 2.4-GHz/5.8-GHz dual-band communication, which greatly improves the stability of the drone connection and enables the drone to better adapt to its environment. The drone can fly smoothly in complex Wi-Fi environments. In the classroom teaching scenario, more drones can be connected simultaneously than before, and the stability of multi-drone formation is enhanced.

Explore more possibilities

Adapter extension board: It provides the 2×7-pin 2.54-mm in-line package interface, supports the I2C, SPI, UART, and GPIO programming protocols, and provides the 5-V/3.3-V power supply. With this board, you can easily add and debug new sensors for more creative ideas.

Born for the Future. More Creative and Intelligent

RoboMaster TT's highly integrated open source extension kit can be used together with its open camera video stream data to implement more diversified AI applications. In addition, by using the new RoboMaster SDK, cutting-edge AI technologies such as machine vision and deep learning can be used in the classrooms of primary and secondary schools. This makes AI more familiar, and enables learning through play for better results with more fun.

Supports External Third-Party Sensors

RoboMaster TT comes with a sensor adapter, which supplies power for third-party sensors. The official DJI SDK is also available to all users in order to support multiple programmable sensor interfaces, such as I2C, SPI, UART, and GPIO. Students can easily expand sensors and develop programs to produce more AI applications.

RoboMaster SDK Based on Python 3.0

With the Python 3.0 RoboMaster SDK, you can easily learn the Python language and program to control drones. You can also use the SDK to create your own applications, implement the interaction between RoboMaster TT and RoboMaster EP, develop your own AI algorithms, and give full play to your creativity.

Supported AI Applications

By adding different third-party sensors to RoboMaster TT, you can customize a variety of creative gameplay.

Environmental perception

Use the infrared ranging technology and obstacle information data to perceive the environment and draw indoor maps. You can learn about the indoor robot navigation technology and automatic obstacle avoidance.

Facial recognition and auto-follow

Obtain the video stream for facial recognition and tracking. You can learn cutting-edge AI technologies, such as machine vision, deep learning, and convolutional neural network.

Gesture recognition

Use gesture recognition sensors and program the drone to obtain gesture information and control actions of the drone. You can learn how the sensor data is read (where separate sensors are required), and implement man-drone interaction.

Palm control

Based on the obtained knuckle movement posture information, develop a program to establish a connection between palm postures and flight actions, and implement palm control (where separate sensors are required). You can understand and learn about microelectronics technology and sensor characteristics.

Perfect Combination of Technology and Art. Easily Set up Multi-Drone Formation

RoboMaster TT supports the Station mode. Therefore, multiple RoboMaster TT devices can be connected to the same Wi-Fi router, receive programming code instructions, and provide feedback, implementing status synchronization and control of multiple drones. You can use the drone for various purposes during teaching, competition, or performance.

Safer

RoboMaster TT adopts a safety-first design and incorporates the following physical and software protection methods to ensure user flight safety: blade protection, precise hovering, and low-battery alarming.

Stabler

RoboMaster TT uses the new 5.8-GHz Wi-Fi module, which features a lower signal transmission delay and better anti-signal-interference performance. On this basis, the multi-drone formation process and experience become smoother.

Simpler

RoboMaster TT supports using graphical programming, Python, and other programming languages for multi-drone formation programming. In addition, students can use the app to easily and quickly set up simple multi-drone formation.

More impressive

With the programmable LED indicators, music, and actions, RoboMaster TT can change lighting colors and their frequencies, delivering an even more impressive multi-drone formation effect.

More fun

With the programmable dot-matrix screen, RoboMaster TT can change patterns on the dot-matrix screen during multi-drone formation to convey unique ideas.

Outstanding Drone and AI. Education Solutions

Backed by innovative and powerful cutting-edge technologies, DJI Education has tailored a professional drone education platform for schools and training agencies. In addition, it has developed industry-leading drone and AI education solutions by combining a series of courses and professional competitions, helping bring students into the intelligent flight world.

Drone and AI Courses

Multidisciplinary integration

The courses integrate science and technology education with mathematics and English, and theoretical learning with practical inquiry, implements the STEAM education approach, and enables students to bring all the learned knowledge together and understand the knowledge thoroughly in the multidisciplinary and interdisciplinary teaching process.

Project-based exploration

By using real-world problems as the context, the courses guide students to take the initiative to explore solutions, cultivate their logical thinking, build their team-work spirit, and improve their problem-solving ability through project-based exploration activities.

Constructivism

Based on Piaget's theory of cognitive development, the courses design learning sections that fit the students' psychological characteristics and cognitive development laws, and combine drone applications with programming skills so that students can learn new knowledge from specific scenarios.

Interest-driven

In the courses, students are inspired to learn about drones and programming independently in a pleasant educational environment, creating more possibilities for students in the future.

Plentiful Drone and AI Competitions

AI Competition

Develop a program to control the drone to automatically cross obstacles and select the correct landing position to implement accurate landing based on the image recognition results. Knowledge points: image recognition and PID control

Air-Ground Operation

The drone conducts reconnaissance in the air and sends the location information to the unmanned vehicle. The unmanned vehicle automatically arrives at the destination and transports materials. Knowledge points: image recognition, air-to-ground communication, and route planning

Maze Race

Develop a program to enable the drone to autonomously explore a way out in a maze with random routes. The maze also contains mission pads with hidden tasks.

Knowledge points: indoor positioning, ToF sensor usage, intra-maze searching, and programmable dot-matrix screen

In the Box

Aircraft  (Propellers included) × 1

RoboMaster TT Propeller Guards × 1

Spare Propeller  (pair) × 2

Dot-Matrix Display & Distance Sensing Module × 1

Open-Source Controller × 1

Extension Board × 1

Mission Pad × 4

Flight Battery × 1

Micro USB Cable × 1

Specs

Drone module

Drone

Take-off weight 87 g (including the propeller blades, propeller blade protector, and batteries)

Dimensions 98×92.5×41 mm

Propeller blade 3''

Built-in functions Infrared height determination, barometer, LED indicator, downward vision sensor, Wi-Fi, and HD 750P image transmission

Interface Micro USB charging port

Flight performance

Maximum flight distance 100 m

Maximum flight spee 8 m/s

Maximum flight time 8 min

Maximum flight height 30 m

Battery 

Removable battery 1.1 Ah/3.8 V

Camera

Image 5 MP

FoV 82.6°

Video HD720P30

Format JPG (for images) and MP4 (for videos)

Electronic image stabilization Supported

Extension accessory

Open source controller

Weight 12.5 g (including the open source controller and ranging dot-matrix screen)

Dimensions 49.5×32×15.2 mm

Operating mode AP and Station modes

Wi-Fi frequency band 2.4 GHz and 5.8 GHz

Bluetooth 2.4 GHz

MCU ESP32-D2WD, dual-core at 160 MHz, 400 MIPS

Open source Supports SDK development, Arduino, graphical programming, and MicroPython programming.

Scalability 14-pin extended interface (for I2C, UART, SPI, GPIO, PWM, and power supply)

Programmable LED indicator Full-color LED

Ranging dot-matrix screen extension module

Dimensions 35.3×31.5×8.6 mm

Programmable dot-matrix LED indicator 8×8 red-and-blue indicator

Dot matrix driving function IIC interface, automatic dot matrix scanning, 256-level adjustable overall brightness, and 256-level adjustable single-LED brightness

Ranging module Infrared distance sensor (ToF)

Maximum distance measured 1.2 m (indoor with white targets)

Adapter extension board

DIY adaptation 14-pin extended interface to the 2×7-pin 2.54-mm in-line pad, 2 power indicator positions, and 2 debugging indicator positions