Collaborative Robot Sensorization with 3D Depth Measurement System for Collision Avoidance

Maria Teresa Calcagni, C. Scoccia, Gianmarco Battista, G. Palmieri, M. Palpacelli
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Abstract

Human-Robot Collaboration (HRC) and Machine Vision are some of the most promising technologies of Industry 4.0. Collaborative robots are quickly gaining ground in the industrial network, due to their possibility of working side by side with humans, in a shared space, without physical barriers. However, the knowledge of the environment is required to adapt the robot motion and guarantee the operator safety. This paper presents a preliminary study for a bigger project regarding the implementation of a full obstacle avoidance strategy into a robotic system for industrial purposes. The system adopted consists of a vision system based on Intel Realsense cameras, an algorithm providing obstacle representation as elementary geometric shapes and an obstacle avoidance strategy used for the motion control of the robot. The continuous monitoring of the operators, objects and robots present in the workstation with the vision system ensures the stability and security of the system.
基于三维深度测量系统的协同机器人防撞传感器
人机协作(HRC)和机器视觉是工业4.0中最有前途的技术。协作机器人正迅速在工业网络中占据一席之地,因为它们可以在共享空间中与人类并肩工作,没有物理障碍。然而,需要对环境的了解来适应机器人的运动并保证操作员的安全。本文提出了一个关于在工业用途的机器人系统中实施完全避障策略的更大项目的初步研究。所采用的系统由基于英特尔Realsense摄像头的视觉系统、以基本几何形状表示障碍物的算法和用于机器人运动控制的避障策略组成。使用视觉系统对工作站内的操作人员、物体和机器人进行持续监控,确保了系统的稳定性和安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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