Abstract: The aggravating trend of an aging population impacts industrial production and social services. Robots are expected to be able to work not only in highly structured manufacturing environments but also in human-inhabited environments, and hence, need to have more sophisticated cognitive abilities. They have to be able to operate safely and efficiently in unstructured, populated environments and achieve high-level collaboration and communication with humans. Collaborative robots, also referred to as cobots, are a new class of industrial robots that can interact with humans in shared spaces or work safely in the vicinity of humans. Collaborative robots are generally lightweight and edge-rounded with multiple degrees of freedom. Besides, multiple sensors must be integrated and limitations of speed and force must be set to ensure their behavior safety. Collaborative robots have shown good application prospects in many fields, such as flexible manufacturing, social services, medical care, disaster prevention, and antiepidemic. They have received wide attention in the industry and academia. Collaborative robots require the integration of multimodal sensory information and intelligent control methods to ensure efficient collaborative behavior. Human-robot collaboration (HRC) considers key issues attached to how safe and efficient collaboration between cobots and humans can be achieved, involving robotics, cognitive sciences, machine learning, artificial intelligence, philosophy, and others. HRC has been included in the key support research programs such as Smart Manufacturing 2025 and the Development Plan of New Generation Artificial Intelligence, recently becoming an important research direction in the field of intelligent robotics with a wide range of applications. This paper introduces several domestic and foreign collaborative robots and intelligent control methods of collaborative robots, including control methods based on perception information, high accuracy tracking control methods, and interaction control methods. It also discusses human intention estimation and robot skill learning methods for efficient human-robot collaboration. Finally, future directions of collaborative robots are explored.