Colour sorting ROS-based robot evaluation under different lights and camera angles

Abstract

Automated colour sorting, aided by mobile robots, is widely prevalent in the current manufacturing industry. Obstacles, such as fluctuating light conditions and camera angles, frequently hinder this procedure. Creating a colour sorting robot is a complex and time-consuming task, especially due to the vulnerability of the RGB colour space to detection errors in extreme brightness or darkness. In response to these concerns, we introduce a mobile robot that operates on the robot operating system (ROS) platform and incorporates OpenCV. This robot employs the hue, saturation, and value (HSV) colour space model for its image processing capabilities in recognising the colours and Welzl’s algorithm for the ball’s diameter estimation. The robot’s performance was assessed across various luminous fluxes and camera tilt angles. It demonstrated exceptional performance at 64 lm and a tilt angle of 40 degrees, achieving an average accuracy of 87.5% for detecting the colour of the ball, and 81.25% for determining its location based on colour. For the ball’s diameter estimation, it was found that the best estimation was received at 64 lm and 30 degrees, with both 96.32%.