Design and Analysis of Laboratory Supervision Robot Based on Robot Operating System

Abstract

As the laboratory becomes more open, the flow of laboratory personnel has increased, which has brought challenges to the daily management of the laboratory. At present, the difficulty of daily laboratory management lies in the cumbersome personnel statistics and the heavy workload of safety monitoring. In response to this problem, this paper proposes a laboratory supervision robot with autonomous movement, autonomous monitoring, face recognition, and management information. First, a face recognition algorithm is designed based on convolutional neural network. Then the robot control system is designed using the robot operating system (ROS). Based on the simultaneous localization and mapping (SLAM) technology, the Gmapping algorithm is used to realize the autonomous movement of the robot, which provides a reference for the design of the laboratory supervision robot.