HECE-IC : an integrated calibration method for delta robot-based kitchen waste sorting systems

Abstract

This paper presents a multifunctional automated sorting system for kitchen waste based on a Delta robot. The sorting system is divided into three main modules: visual detection, information processing, and multifunctional robotic sorting. The visual detection module captures images of waste on a conveyor belt and transmits them in real-time to the information processing unit, where detection algorithms generate data on waste categories and grasp positions. The robotic arm, equipped with a force sensor, gripper, and suction cup, selects appropriate grasping or suction functions based on the waste type and shape to complete sorting. Additionally, this paper introduces a robust and efficient integrated calibration method for robot hand-eye-conveyor belt-encoder systems (HECE-IC), which enables simultaneous hand-eye and encoder calibration with only three simple steps. In simulations, the proposed method maintains a reconstruction error as low as 0.423 mm even under operation errors up to 0.6 mm. In practical experiments on the sorting platform, the average calibration error stabilized around 0.5 mm, achieving high calibration precision. The system achieved a sorting success rate of 90.2% and a sorting speed of 979 objects per hour. Our code is available at: https://github.com/TDA-2030/XRobot