Human-Robot Collaboration With Commonsense Reasoning in Smart Manufacturing Contexts

Human-robot collaboration (HRC), where humans and robots work together to handle specific tasks, requires designing robots that can effectively support human beings. Robots need to conduct reasoning using commonsense knowledge (CSK), e.g., fundamental knowledge that humans possess and use subconsciously, in order to assist humans in challenging and dynamic environments. Currently, there are several effective CSK systems used for organizing information and facts, along with detecting objects and determining their properties. HRC is employed in various manufacturing tasks, such as paint spraying and assembly, in order to keep humans safe while increasing efficiency. Although there is a large array of research on HRC and on CSK, there is minimal research linking the two concepts together. This paper presents a novel system on human-robot collaboration guided by commonsense reasoning for automation in manufacturing tasks. This fits within the general realm of smart manufacturing. The primary focus is on improving the efficacy of human-robot co-assembly tasks. Evaluations conducted with online simulations and real-world experiments indicate that reasoning using CSK-based robot priorities enhances HRC as compared to simpler robot priorities, e.g., merely handling nearby objects. This system is modifiable and can be used for larger and more complex real-world tasks, thereby leading to improved automation in manufacturing. This paper demonstrates the scope of combining HRC and CSK, while future works will be able to further utilize the benefits of combining the two fields with significant impacts. Note to Practitioners - This paper is motivated by the human-robot collaboration problem in smart manufacturing. Robots operating by reasoning with commonsense priorities in human-robot collaboration enable faster task execution and better human work life. This can help balance work for humans and prevent injury. Adding robots to tasks accordingly does not necessarily decrease costs, but can limit human exposure to danger which is significant (and can also lower costs overall). Simulations and real-world experiments in our research using commonsense reasoning demonstrate how work is easier and better with human-robot collaboration. These factors are highly significant when tasks are repeated multiple times. The system is presented within automated manufacturing and is scalable for different real-world applications. Such automation is particularly helpful during recent times in the aftermath of the COVID-19 pandemic.