Human-Robot Collaboration

Human-robot collaboration studies how people and robots share tasks, information, and control in settings such as manufacturing, assembly, transport, healthcare, and remote operation. Common approaches combine compliant or shared control with perception of human motion, intent, fatigue, and attention; task planning and assistance may use reinforcement learning, motion prediction, or vision-language models. Researchers evaluate these systems in physical workcells, simulated tasks, teleoperation studies, and user experiments, measuring safety and task performance alongside workload, trust, agency, and coordination. A central challenge is balancing proactive autonomy and efficiency with predictable behavior, robust safety, and meaningful human oversight, especially when methods tested in simulation must transfer to real people and workplaces.