The Application of Artificial Intelligence in Indoor Positioning and Scene Reconstruction of Robots

The powerful functions of robots in life and production have been proven. It can replace humans to perform some complex and dangerous tasks, and it can also perform related tasks in some dangerous areas. Traditional robot systems rely on GPS systems for information transmission and command sending and receiving. People can monitor the status of the robot's task execution in real time through the computer's host computer system. However, for some relatively closed areas or areas with poor signal, this limits the use of the robot. With the continuous development of sensor technology and visual positioning system, robots have begun to develop towards autonomous positioning and scene reconstruction. This research uses the CNN algorithm of artificial intelligence theory and the GRU method to design an intelligent recognition system, which can also assist the computer system to monitor the task execution process of the robot. It can also monitor the robot's autonomous positioning and scene reconstruction information. The research results found that CNN and GRU technology can assist the robot to identify the characteristics of indoor related objects, and the maximum error rate is only 2.439%. This part of the error is reliable enough for the robot to complete the tasks of autonomous positioning and scene reconstruction. © 2023 CAD Solutions, LLC.