Study Reveals FNN and GA Enhance Intelligent Robot Navigation

In recent years, the integration of artificial intelligence (AI) and computer technology has significantly advanced the development of intelligent robots. These technologies have not only supported the growth of intelligent robots but have also expanded the application of AI across various industries. The rise of intelligent robots, a product of the new industrial revolution, has become a driving force in sectors such as automation, logistics, and healthcare, showcasing immense potential.

As the demand for intelligent applications and smart management systems increases, AI and computer technology have become essential for sustainable development. The research on AI and computer technology has become a focal point in global science and technology, with continuous advancements and breakthroughs. Despite significant progress in integrating AI and computer technology, challenges persist in practical applications, particularly in areas like intelligent robot navigation and path planning.

To address these challenges and enhance the navigation accuracy and path planning efficiency of intelligent robots in complex environments, a study has proposed a method that combines fuzzy neural network (FNN) and genetic algorithm (GA). The FNN algorithm aims to improve navigation accuracy, while the GA optimizes path planning efficiency to ensure the robot can navigate efficiently in dynamic and intricate environments. By comparing various navigation methods, including BP neural network (BPNN), self-organizing map network (SOM), and adaptive resonance theory neural network (ART), the study demonstrated that the FNN and GA algorithm model significantly enhances navigation accuracy and efficiency.

The experimental results showed that the intelligent robot based on the FNN algorithm achieved high navigation accuracy of 98.64%, with a minimal error angle deviation of 1.52% and a short navigation time of 9.64 seconds. The integration of FNN and GA in path planning enabled the robot to achieve the shortest path planning time and highest efficiency, driving further advancements in the field of intelligent robots.

Furthermore, the study highlighted the importance of AI and computer technology in the development of intelligent robots. By applying advanced algorithms and techniques like neural networks and genetic algorithms, researchers have unlocked new possibilities for enhancing the performance and autonomy of intelligent robots. These technologies have found applications in various industries, including industrial automation, logistics, agriculture, and service sectors, where intelligent robots play crucial roles in improving operational efficiency and delivering innovative solutions.

Moving forward, the continuous innovation and exploration of AI and computer technology in the field of intelligent robots will open up new opportunities for advancements in automation, robotics, and smart technologies. By leveraging the synergies between these technologies, researchers and industry experts can drive further progress in intelligent robot technology, paving the way for enhanced capabilities and broader applications in diverse fields.