Application and Challenges of Artificial Intelligence in Quadruped Robots

This article focuses on the application of artificial intelligence in quadruped robots, and the main achievements are as follows. Optimization of reinforcement learning algorithms: It makes up for the lack of intelligence in traditional control methods. Bionic and bio-inspired strategies: Enhance the natural motion characteristics of the robot. Multimodal perception fusion and intelligent navigation technologies: With the help of technologies such as thermal field path planning and edge computing, it promotes the improvement of the autonomous capabilities of quadruped robots. Problems and challenges: There is still room for improvement in aspects such as the transfer efficiency between the simulation and real environments, the real-time computing ability under the dynamic constraints of hardware, as well as the safety and robustness in complex scenarios. This article aims to provide technical directions and theoretical references for the future research on quadruped robots.