高校机械类实验室安全预警与监测智能巡检机器人设计

Design of intelligent inspection robot for safety warning and monitoring of mechanical laboratories in universities

该文针对高校机械类实验室安全风险,设计了智能巡检机器人。首先改进Cartographer算法实现巡检机器人自主建图与导航;然后改进PANet分割算法,实现基于热力图对目标进行分割;最后将长短期记忆网络(LSTM)算法与选择性搜索算法融合识别人体动作,实现实验行为识别与监测。通过横向对比巡检机器人检测、人工定期检测和人工随机检测三种情况下识别各类安全隐患的次数与准确度,证明智能巡检机器人具有较大优势。

This paper designs an intelligent inspection robot for the safety risk of mechanical laboratories in universities.Firstly,the Cartographer algorithm is improved to realize autonomous map building and navigation of the inspection robot;then,the PANet segmentation algorithm is improved to realize segmentation of the target based on the heat map;finally,the long short-term memory network(LSTM)algorithm is fused with the selective search algorithm to recognize the human body movements,and to realize the experimental behavior recognition and monitoring.By comparing the number of times and accuracy of identifying various types of safety hazards in the three cases of inspection robot detection,manual periodic detection and manual random detection horizontally,it proves that the intelligent inspection robot has a greater advantage.