At the opening of Bett 2026 in London, DFRobot presented a series of hands-on robotics and artificial intelligence projects aimed at supporting STEM education across primary and secondary school levels. The demonstrations are being shown at the ExCeL Centre and focus on making AI concepts tangible through physical interaction with robots and sensors.
A central theme of the exhibit is the use of robots to illustrate how AI systems perceive their environment and translate observations into actions. One example is a vision-based autonomous driving project built around a small mobile robot equipped with an AI vision sensor. Instead of following predefined paths, the robot navigates by identifying obstacles and planning routes based on visual input, exposing students to the full decision-making loop used in autonomous systems.
Several projects focus on computer vision as an entry point to AI literacy. Using a trainable vision sensor, students can experiment with gesture recognition, object detection, and pose tracking. In one demonstration, hand gestures are used to control a simple game without relying on traditional input devices. In another, a robot mirrors human arm movements in real time, showing how visual recognition can directly control physical systems.
The exhibit also includes applied scenarios that link AI to real-world problems. Demonstrations range from a simulated smart feeder that distinguishes between different animals to a wildlife observation setup that uses night vision to detect animals in low-light conditions. These examples are designed to show how AI models can be trained and deployed in environments that reflect practical constraints rather than ideal classroom settings.
In a separate area, DFRobot highlights introductory tools intended for younger students. These tools allow learners to explore basic AI concepts such as detection and classification through direct interaction with objects, without requiring programming skills. The approach is positioned as a pathway from exploratory learning toward more structured coding environments using widely adopted educational platforms.
The demonstrations at Bett 2026 reflect a broader trend in STEM education toward combining robotics, AI, and hands-on experimentation. By using small-scale robots and on-device AI processing, the projects aim to help students understand how abstract algorithms connect to physical systems and real-world applications.
