Self-driving Educational Robot


The autonomous driving education robot APOLLO, developed independently by Bayes Robotics, is equipped with high-end industry hardware and integrates 30 leading AI technologies into classroom teaching. Combined with the BayesStudio software platform, Python practical teaching materials, and supplementary teaching resources, it allows teachers and students to experience AI applications, learn AI technology, and master Python programming knowledge through practical learning, thereby facilitating the implementation of AI education in schools at all levels.

Product Features

Autonomous Navigation and Obstacle Avoidance

Utilizing multiple sensors such as laser radar and ultrasonic sensors, it achieves autonomous and precise navigation while ensuring safety through obstacle avoidance.

Powerful Language System

Utilizing spatial array beamforming and noise reduction technology, APOLLO can hear, understand, and fulfill your needs effectively.

Core Motion System

Incorporating closed-loop control algorithms with multiple sensors like IMU (Inertial Measurement Unit) and odometers, coupled with a robust power unit, ensuring smoother and more stable movement.

Voice and Visual Interaction

The robot can engage with students through natural language communication, answering questions, providing guidance, and explaining complex concepts and technologies.

Computational Display System

With a powerful computational display system, it can confidently handle various complex environments and efficiently execute a wide range of tasks.

Flexible Social Interaction

The robot can connect to a learning community, allowing students to interact with each other, promote collaborative learning, and collectively progress together.


Product Specifications

Basic Parameters
Operating Temperature
0°C to 50°C
RAM (Memory)
ROM (Storage Capacity)
Screen Size
11.6 inches IPS
Performance Parameters
Screen Resolution
Movement Speed
Default 0.5m/s, maximum 0.8m/s
Battery Capacity
25.2V 15Ah Lithium Battery
Drive Mode
Two-wheel differential
Obstacle Clearance

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