In order to realize the remote monitoring of robots, a remote monitoring platform for industrial robots is designed based on the browser/server (B/S) architecture. Through this platform, users can check the real-time running parameters and running status of robots in any place with network. The Industrial Internet of Things scheme of remote platform system is proposed to adopt three-layer structure: on-site “perception layer,” information “transmission layer,” and remote data service center. The data acquisition controller of the whole system and the core part of the sensor layer is designed. The data acquisition controller adopts the embedded platform design, which can be directly connected with the control cabinet of the industrial robot to read the running status of the robot in real time, monitor the alarm and warning data, and it is transmitted to the local server and remote service center in the first time. At the same time, the robot can receive the control command of the server for remote debugging and fault maintenance. Aiming at the data model of industrial machinery parts, a fault prediction method based on BP neural network algorithm is proposed. According to the needs of the target algorithm and the analysis of the measurement results, an attempt is made to obtain a more feasible fault diagnosis and early warning method. Through the remote monitoring system, fault early warning and corresponding troubleshooting methods are realized.

With the rapid development of the information age, the development of industrial robots is also advancing by leaps and bounds. In the scenes of automobile, medicine, aerospace, and public service, we have fully enjoyed the convenience brought by industrial robots. However, with the continuous development of industrial robot-related concepts and technologies, human-computer interaction and cooperation have become the development trend of industrial robot. In this paper, the human-machine cooperation and path optimization of industrial robot in a complex road environment are studied and analyzed. At the theoretical modeling level, firstly, the industrial robot is modeled and obstacle avoidance is analyzed based on the kinematics of industrial robot; thus, an efficient and concise collision detection model of industrial robot is proposed. At the algorithm level, in view of the complex road conditions faced by industrial robots, this paper will study and analyze the obstacle avoidance strategy of human-computer cooperation and real-time path optimization algorithm of industrial robots. Based on the virtual target point algorithm, this paper further improves the problem that the goal of the traditional path planning algorithm cannot be fully covered, so as to propose the corresponding improved path planning algorithm of industrial robots. In the experimental part, based on the existing industrial robot system, the human-machine cooperation and path planning system proposed in this paper are designed. The experimental results show that the algorithm proposed in this paper improves the accuracy of obstacle avoidance by about 10 points and the corresponding convergence speed by about 5% compared with the traditional algorithm and the experimental effect is remarkable.