Analysis of an Intelligent Robotic Grasping System for Waste Sorting

The increasing global municipal solid waste generation and the limitations of manual sorting underscore the urgent need for intelligent robotic solutions. This paper systematically analyzes intelligent robot grasping systems for garbage sorting, focusing on the synergistic integration of key technologies: multimodal perception fusion (vision and tactile), adaptive shared control, and soft gripper design. The review highlights that combining visual perception for global localization with tactile feedback for fine force adjustment significantly enhances grasping success in cluttered scenes. Furthermore, human-machine collaborative control balances operational efficiency with safety, while compliant soft grippers improve adaptability to irregular objects. Experimental validations demonstrate that such an integrated system architecture effectively improves robustness and operational performance in unstructured environments. This analysis provides a comprehensive technological reference and a viable pathway for deploying reliable intelligent grasping systems in practical waste sorting applications, contributing to environmental protection and the circular economy.