With the increasing scale and complexity of energy storage stations, traditional manual inspection methods can no longer meet safety and maintenance requirements. Quadruped robots, with their excellent all-terrain adaptability, have become an ideal choice for intelligent inspection of energy storage stations. This paper reviews path planning and navigation technologies for quadruped robots in complex energy storage station environments, including LiDAR SLAM, multi-sensor fusion localization, motion planning, and obstacle avoidance methods, and discusses the possibility of multi-robot collaborative operation to provide references for energy storage station intelligent inspection system design. By analyzing mainstream LiDAR odometry techniques, we propose optimization directions for quadruped robot navigation systems in complex energy storage station environments, aiming to solve the positioning problems of traditional methods in feature-scarce environments and improve inspection efficiency and accuracy.