# CAS Institute of Automation proposes tactile-enhanced grasp-and-insertion framework, achieving 67% success rate at 0.05 mm clearance

- Source: 帕西尼 · 微信公众号
- Published: 2026-10-30T03:44:29.000Z
- RoboHot: https://robohot.news/en/items/mprbcvfsy3uuyknckbi3mhnb4
- Original: https://mp.weixin.qq.com/s?__biz=MzkzODI5NDkwMw==&mid=2247492542&idx=1&sn=66dd2aab20031be7de566cce0d4f63e3&chksm=c30bd5ba4d7ae014e43cf8ef901d8ed5026633d2e5878423f2b151788ba9f8528d6dafea0dec&scene=126&sessionid=1793359854#rd

## Summary

The team led by Cheng Long at the Institute of Automation, Chinese Academy of Sciences, proposed a tactile-enhanced full-pipeline learning framework for grasping and insertion, achieving a 67% success rate at 0.05 mm clearance and a 60% reduction in peak contact force; the paper was accepted to IROS 2026. The research uses the PaXini PX6AX GEN3 multi-dimensional tactile sensor as its core sensing hardware, integrated into a seven-axis robotic arm, covering five geometric shapes and three clearance levels of 1, 0.25, and 0.05 mm. Under the same conditions, the tactile-free IL+RL approach achieved a 52% success rate, while the pure imitation learning approach achieved 0.