# Dynamic grasping system based on visual algorithm and robot arm collaboration in logistics production line

## TL;DR

This paper introduces a new system for dynamic grasping in logistics that uses vision algorithms and robot arms to improve accuracy and efficiency.

## Contribution

The novel VRCDS system combines a multi-feature vision algorithm with multi-robot collaboration for improved dynamic grasping performance.

## Key findings

- VRCDS achieves high recognition accuracy and robust grasping efficiency across varying conveyor speeds.
- The system demonstrates precise trajectory control and significant power consumption reduction.
- It outperforms traditional single-arm and visual servo systems in logistics automation tasks.

## Abstract

In response to the urgent need for efficient and accurate dynamic grasping in automated logistics, this study proposes the VRCDS, a dynamic grasping system that integrates a multi-feature weighted PnP vision algorithm with multi-robot arm collaboration. The system establishes a closed-loop “perception-decision-execution-feedback” architecture, significantly enhancing grasping accuracy, system efficiency, and energy savings compared to traditional single-arm or visual servo schemes. Experimental results demonstrate that the VRCDS system achieves high recognition accuracy, robust grasping efficiency under various conveyor speeds, precise trajectory control, and a substantial reduction in power consumption. The research provides an efficient, precise, and reliable solution for dynamic grasping tasks in logistics automation.