https://www.sciencedaily.com/releases/2021/04/210407124010.htm

Instead of being able to only judge distance between itself and its human co-workers, the human-robot collaboration system can identify each worker it works with, as well as the person's skeleton model, which is an abstract of body volume, says Hongyi Liu, a researcher at KTH Royal Institute of Technology. Using this information, the context-aware robot system can recognize the worker's pose and even predict the next pose. These abilities provide the robot with a context to be aware of while interacting.

Liu says that the system operates with artificial intelligence that requires less computational power and smaller datasets than traditional machine learning methods. It relies instead on a form of machine learning called transfer learning -- which reuses knowledge developed through training before being adapted into an operational model.