Motion attitude control algorithm of mobile robot

Mobile robots have found increasing applications across various sectors, with their motion control technology evolving from classical to intelligent methods. Classical control algorithms, while simple and mature, face limitations in complex and dynamic environments. Modern intelligent control techniques, including deep reinforcement learning and Transformer architectures, offer enhanced adaptability. This paper systematically presents mainstream motion control algorithms for mobile robots, analyzing their characteristics, applications, and development trends, while also addressing current technical bottlenecks and future research directions.