Abstract: Following robots, as a significant branch of service robotics, have demonstrated broad application prospects in scenarios such as factory inspection and logistics transportation in recent years. This paper presents a comprehensive review of key technologies in following robots, covering four core modules: perception, control, SLAM, and path planning. In the perception module, it summarizes sensor fusion methods involving LiDAR, mono/stereo vision, and UWB, and analyzes their applicability and limitations. In terms of control, it reviews strategies such as impedance control, admittance control, optimal control, and deep reinforcement learning, focusing on the trade-offs between robustness and human-robot interaction. For localization and mapping, the paper compares the integration of LiDAR/visual SLAM with wireless positioning techniques. In the path planning module, various optimization algorithms and heuristic search strategies are analyzed for their effectiveness in dynamic environments. Moreover, this review identifies and categorizes major technical challenges, including perception degradation under environmental disturbances, response delay due to rapid target motion, accumulated errors in long-term following, and insufficient naturalness in human-robot interaction. Representative solutions addressing these issues are also summarized. Finally, the paper outlines future research directions, emphasizing improvements in multimodal perception robustness, intelligent interaction, autonomous energy management, and collaborative mechanisms in multi-robot systems.