arXiv:2508.14763cs.RO2025-08被引 2

让机器人在屠宰车间安全协作,还能让工人看懂它在干什么。

Safe and Transparent Robots for Human-in-the-Loop Meat Processing

  • 用视觉+力觉传感器实时监测人和刀具,确保安全停机。
  • 通过灯号和界面提示不确定性,让工人随时掌握机器决策。
  • 适合想提升自动化但又担心安全与透明度的食品加工企业。

劳动力短缺严重冲击肉类加工业。自动化技术有望缓解这一问题,但现有方案高度专用、灵活性差且成本高昂。本文提出通用型协作机器人系统,可与人类协同完成多种肉类加工任务。基于行业专家调研,我们识别出两大挑战:一是保障人类工友安全,二是让工人理解机器人行为。为此,我们构建了兼顾安全与透明性的框架:采用手部检测系统持续监控人员接近,触发紧急停机;使用带力传感器的智能刀具区分肉、骨与夹具;引入不确定性检测机制,通过LED灯信号向人类传达判断置信度,并设计可视化界面展示机器人切割计划,支持人工反馈。用户研究验证了该框架在保障安全与保持人机协作透明性方面的有效性。

原文摘要 · Abstract (English)

Labor shortages have severely affected the meat processing sector. Automated technology has the potential to support the meat industry, assist workers, and enhance job quality. However, existing automation in meat processing is highly specialized, inflexible, and cost intensive. Instead of forcing manufacturers to buy a separate device for each step of the process, our objective is to develop general-purpose robotic systems that work alongside humans to perform multiple meat processing tasks. Through a recently conducted survey of industry experts, we identified two main challenges associated with integrating these collaborative robots alongside human workers. First, there must be measures to ensure the safety of human coworkers; second, the coworkers need to understand what the robot is doing. This paper addresses both challenges by introducing a safety and transparency framework for general-purpose meat processing robots. For safety, we implement a hand-detection system that continuously monitors nearby humans. This system can halt the robot in situations where the human comes into close proximity of the operating robot. We also develop an instrumented knife equipped with a force sensor that can differentiate contact between objects such as meat, bone, or fixtures. For transparency, we introduce a method that detects the robot's uncertainty about its performance and uses an LED interface to communicate that uncertainty to the human. Additionally, we design a graphical interface that displays the robot's plans and allows the human to provide feedback on the planned cut. Overall, our framework can ensure safe operation while keeping human workers in-the-loop about the robot's actions which we validate through a user study.

机器人协作食品安全人机交互智能装备

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