Multimodal perception-fusion-control and human–robot collaboration in manufacturing: a review

Abstract

Collaborative robots, also known as cobots, are designed to work alongside humans in a shared workspace and provide assistance to them. With the rapid development of robotics and artificial intelligence in recent years, cobots have become faster, smarter, more accurate, and more dependable. They have found applications in a broad range of scenarios where humans require assistance, such as in the home, healthcare, and manufacturing. In manufacturing, in particular, collaborative robots combine the precision and strength of robots with the flexibility of human dexterity to replace or aid humans in highly repetitive or hazardous manufacturing tasks. However, human–robot interaction still needs improvement in terms of adaptability, decision making, and robustness to changing scenarios and uncertainty, especially in the context of continuous interaction with human operators. Collaborative robots and humans must establish an intuitive and understanding rapport to build a cooperative working relationship. Therefore, human–robot interaction is a crucial research problem in robotics. This paper provides a summary of the research on human–robot interaction over the past decade, with a focus on interaction methods in human–robot collaboration, environment perception, task allocation strategies, and scenarios for human–robot collaboration in manufacturing. Finally, the paper presents the primary research directions and challenges for the future development of collaborative robots.