SHANGHAI, May 28, 2020 /PRNewswire/ -- DFRobot is launching micro:Maqueen Plus this week, the newest offer of its popular educational robot series of micro:Maqueen. The new product, adopting machine learning technology, is designed for K-12 educators to teach AI through teaching AI.
The Maqueen Plus is different from other educational programming robots on the market, for it is equipped with AI capable of machine learning and visual recognition. It is able to continuously improve its abilities to recognise lines, colours, signs, QR codes, etc. Maqueen Plus has become smarter and performs better in circumstances such as autopilot. This whole process provides a direct and detailed experience for students to explore ideas and outputs of AI technology.
With micro:Maqueen Plus, students can assemble a self-driving robot car by themselves. The body of Maqueen Plus contains few parts which can be assembled within minutes. The AI-powered 'eye', an AI vision sensor which gives the car recognition abilities, is only one click away from becoming smart--with the learning button pressed, the sensor begins observing targets in its frame and learning to recognize the target with built-in AI visual ability.
"The best way to learn AI is to teach AI," said Liu, product manager of micro:Maqueen Plus. "We are looking for a feasible approach to introduce AI technology to today's STEM classroom. Being a STEM-based hardware, the first thing Maqueen Plus does is to make it possible for students to build physical projects, rather than just talking about AI technology in theory. In order to make it easy to incorporate with, the robot is compatible with popular platforms like micro:bit, so teachers don't have to spend much time on further trainings of robotics or AI-related algorithms. What's more, the robot is designed as a reusable educational hardware, with a friendly price no higher than current programming educational robots on the market that have no AI-based design."
Liu suggested that compared to previous micro:Maqueen, Maqueen Plus provides more flexible AI robot teaching programs, more functions and expansion ports. It has better power management, larger power supply capacity and chassis. Carrying abundant scientific and technological knowledge, it is not only suitable for classroom teaching, but can also be used for after school exercises and robot competitions.
