The interactive control of lower limb exoskeleton robots (LLERs) is important to achieve compliance and safety. Significant challenges in the interactive control of LLERs include how to accurately recognize human motion intention, how to accurately recognize the motion environment, and how to achieve natural, stable, and accurate interactive control in accordance with the human motion intention and the environment. This article presents a detailed classification of motion intention recognition, interactive control based on motion intention, and interactive control based on the LLER's motion environment and summarizes the methodologies in each category. In addition, the advantages and disadvantages of motion intention recognition, motion environment recognition, and interactive control based on the motion intention and motion environment are analyzed from a macroscopic perspective, and current trends are discussed. Finally, this article explores which requirements should be met in future LLER applications to improve the naturalness, stability, and accuracy of interactive control.