In the realm of computer technology and artificial intelligence, the fusion of these two domains has paved the way for remarkable advancements in the field of intelligent robots. The application of fuzzy neural network (FNN) and genetic algorithm (GA) has revolutionized navigation and path planning for intelligent robots, offering unparalleled precision and efficiency in complex environments.
The historical context of this technological evolution is rooted in the increasing societal demand for intelligent applications and management systems. As a product of the new industrial revolution, intelligent robots have emerged as a driving force in various sectors such as automation, logistics, and healthcare. The integration of AI and computer technology has become a focal point in global scientific and technological development, leading to a surge of research and innovation in related fields.
The primary objective of this study was to address the challenges faced by intelligent robots in navigation and path planning. By combining FNN and GA, a novel method was proposed to enhance navigation accuracy and optimize path planning efficiency. The FNN algorithm significantly improved navigation accuracy in complex environments, achieving an impressive accuracy rate of 98.64% and minimizing error angle deviation to 1.52%. On the other hand, the GA algorithm streamlined path planning, ensuring the shortest navigation time of 9.64 seconds and the highest efficiency.
The experimental results showcased the superiority of the FNN and GA model in intelligent robot technology. The collaborative approach not only enhanced navigation accuracy but also expedited path planning, propelling the further development of intelligent robots. The integration of these cutting-edge technologies has opened up new possibilities for the industry, offering enhanced performance and adaptability in dynamic and challenging environments.
Furthermore, the study delved into the historical progression of intelligent robot research, shedding light on the advancements made in various nations. From the analysis of intelligent robot technologies to the exploration of theoretical frameworks, the study emphasized the need for practical integration and real-world application of these innovations. By leveraging AI and machine learning advancements, the study aimed to bridge the gap between theoretical research and practical implementation, laying the foundation for a new era of intelligent robotics.
In conclusion, the seamless integration of artificial intelligence and computer technology has propelled the field of intelligent robots to new heights. The innovative application of FNN and GA algorithms has revolutionized navigation and path planning, setting a new standard for precision and efficiency in intelligent robot operations. As the industry continues to evolve, the future holds immense potential for further advancements in AI-driven robotics, revolutionizing automation, logistics, and service industries. The journey towards intelligent automation is well underway, with AI and computer technology leading the way towards a future where intelligent robots play a pivotal role in shaping our world.
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