Abstract
The robot is a very complex multi‐input multioutput nonlinear system. It has time‐varying, strong coupling, and nonlinear dynamic characteristics, and its control is very complicated. Due to the inaccuracy of measurement and modeling, coupled with changes in the load and the influence of external disturbances, it is actually impossible to obtain an accurate and complete dynamic model of the robot. We must face the existence of various uncertain factors of the robot. This paper analyzes the real‐time communication protocol in the wireless network control system and confirms that the main way to improve the real‐time performance of the wireless network control system is to implement the real‐time media access control (MAC) protocol. This paper studies robots from the perspective of control and mainly discusses how to use artificial immune algorithms to design robust nonlinear proportion integral derivative (PID) controllers. A nonlinear PID controller is used to replace the classic PID controller. The nonlinear link can be adjusted with the change of the error, so as to achieve the purpose of improving the adaptability and robustness to obtain satisfactory tracking performance. We carried out selective compliance assembly robot arm (SCARA) robot remote control experiment, dual robot following experiment, SCARA and ABB robot collisionless motion planning experiment, and multirobot intelligent collaborative assembly experiment. The experimental results show that the C/S mode remote control system has good practicability and can complete remote tasks; the P2P communication system has good information transmission effects and can realize real‐time information sharing between robots; the collision‐free motion planning algorithm enables the dual robots to complete obstacle avoidance tasks well in complex operating environments; the functional modules of the system can closely cooperate to complete the tasks in coordination, and the multirobot system has a certain degree of intelligence.
Highlights
As an emerging research discipline, intelligent robots cover various disciplines such as robot kinematics, biological simulation disciplines, artificial intelligence technology, and sensor technology and play an important role in the development of society and the progress of human life [1]
As an important tool for future social development, intelligent robot technology plays a prominent role in many fields [3,4,5]
In the realization of wireless sensor networks, network selflocalization is very important and is the key technology for realizing target positioning and tracking; the communication between mobile robots and wireless sensor networks is the prerequisite for realizing feedback control of mobile robots
Summary
As an emerging research discipline, intelligent robots cover various disciplines such as robot kinematics, biological simulation disciplines, artificial intelligence technology, and sensor technology and play an important role in the development of society and the progress of human life [1]. Intelligent robots can autonomously complete difficult and tedious industrial tasks by acquiring and processing external information. As the environment changes, new environment models can be established and revised to complete various tasks [2]. As an important tool for future social development, intelligent robot technology plays a prominent role in many fields [3,4,5]. The application of intelligent robots in the manufacturing field can increase output with high efficiency and successfully promote the development of intelligent production systems and the intelligent life of humans in the future. The most important part of an intelligent robot system is the learning module of the robot, which is an important factor in the intelligentization of the robot [6, 7]
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