ROBOCYCLE用双臂机器人自动分拣垃圾，能抓取易变形物品。
ROBOCYCLE: Autonomous Dual-Arm Robotic Manipulation and Coordination for Recycling Applications
- 多视角视觉+Transformer分割，精准识别杂乱垃圾
- 90.3%抓取成功率，84.3%任务完成率，可拧开瓶盖
- 适合城市垃圾站等真实复杂环境，可扩展部署
随着城市垃圾量增加和人力短缺加剧，自动化分拣系统成为刚需。但现有机器人在感知与操作透明、易变形或杂乱物体时仍存在困难。本文提出ROBOCYCLE，一种面向东京都市区回收标准的自主双臂机器人平台。系统融合多视角RGB-D感知、基于RF-DETR的实例分割以及通过Anygrasp SDK实现的6-DoF抓取规划。通过对分割后的点云处理，生成针对不规则和易变形废弃物的鲁棒候选位姿。实验显示，系统抓取成功率达90.3%，整体任务成功率84.3%，可完成如拧开PET瓶盖等复杂协同操作。该平台为真实人机共存环境下的自主废物管理提供了可扩展解决方案。
原文摘要 · Abstract (English)
As urban waste volumes escalate and labor shortages intensify, automated waste sorting systems are becoming a necessity. However, current robotic solutions often struggle with the 3D perception and manipulation of transparent, deformable, or cluttered objects. This work introduces ROBOCYCLE, an autonomous dual-arm robotic recycling platform designed to meet the recycling standards of the Tokyo metropolitan area. Our approach integrates multi-view RGB-D perception, transformer-based instance segmentation using RF-DETR, and 6-DoF grasp planning via the Anygrasp SDK. By processing segmentated point clouds, the system generates robust candidate poses for irregular and deformable waste. The system achieved a 90.3% grasp success rate and 84.3% overall task success rate, effectively performing complex coordinated tasks such as unscrewing PET bottle caps. The proposed platform offers a scalable solution for autonomous waste management in real-world human environments.
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