From "Seeing" to "Understanding," SingTown Technology Drives Visual Advancement

In the application of intelligent service robots, environmental perception and target recognition are key technologies for achieving autonomous interaction and task execution.

The robot needs to recognise multiple objects in complex indoor environments, such as room doors and their open/closed status, human gestures, QR codes, and typical objects in daily scenarios (e.g., tabletops, items, markers, etc.). To achieve this, service robot manufacturers plan to adopt SingTown Technology's OpenMV smart camera to build a multi-target recognition system based on machine vision. Installed on the robot's head or body, the system can capture images in specified directions in real-time according to master control instructions, identify target categories, dimensions, and colour features, and return the recognition results to the host for path decision-making, task triggering, or voice interaction responses. Additionally, it can be extended to recognise QR codes for navigation positioning, task identification, or authentication, helping robots achieve higher-level intelligent behaviours in areas such as daily life, security, and guided tours.

Service robot manufacturers have developed a multi-target recognition system based on SingTown Technology's OpenMV intelligent camera, enabling service robots to achieve intelligent visual perception in complex scenarios. This system integrates computer vision, AI image recognition, template matching, colour tracking, morphological analysis, and QR code decoding algorithms.

The system captures real-time images of the robot's forward field of view through the camera. Edge-side AI utilizes object detection models to identify object edges and shape features, enabling the determination of door positions and open/closed statuses. Through color segmentation and brightness variation analysis, it can recognize the colors, dimensions, and relative distances of various objects.

This robot can also recognise gestures. Under close-range conditions, the system, based on contour tracking and key point matching algorithms, can identify common actions (such as raising a hand, pointing, waving, etc.). Simultaneously, the built-in QR code recognition function enables the robot to identify navigation points or receive task instructions.

This system can achieve edge deployment, with its algorithm operating efficiently in embedded environments, achieving a frame rate of over 20fps and a recognition latency below 100ms.

The system can communicate with the main control microcontroller via serial port, I²C, or CAN bus, outputting recognition categories, dimensions, colours, and status information to achieve intelligent linkage with the host.

Test results indicate that the solution developed based on SingTown Technology's OpenMV smart camera achieves an indoor recognition accuracy rate of over 92% under varying lighting conditions. It supports multiple task scenarios, such as home companion robots, security patrol robots, and guide robots, significantly enhancing the robot's environmental understanding and interaction capabilities.