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Human-Robot Interaction

Human-Robot Interaction & Teaming

Cognitive HRI, physical human-robot interaction, multi-agent human-robot teaming, human-robot decision making, and human-security robot interaction.

Improving the way humans and machines work together can help democratize robotics. Robots will be able to adapt to new human users, regardless of their expertise — even as the robots adapt to new tasks, situations, and environments. The right design and interface can put the power of robotics in the hands of those who need it, whether it is helping a factory manager with product lines or an artist with a new painting.

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This multidisciplinary work integrates the cognitive, emotional, and physical dimensions of collaboration to expand human productivity.

The basis of any relationship is trust, and it’s no different for a human and robot. A focus in this field is the study of trust between people and autonomous systems. Researchers develop sophisticated frameworks to estimate, calibrate, and monitor trust in real-time, for example between a driver and autonomous vehicles. This includes studying how robot personality, perceived gender, and explanations influence human acceptance, anxiety, and stress.

Faculty also design social robots for a range of uses: stimulating creativity in children, supporting adolescent mental health, or assisting in geriatric care through long-term. It is often important that the end-users are heavily involved in the design process. Relatedly, researchers also work on socially aware navigation. This can enable robots to move through dense crowds or navigate public spaces like museums without breaking typical patterns of human movement.

In areas where humans and robots must work together to accomplish a task, researchers study predicting human intent. Models are developed that track motion and utilize human gaze data to infer intent, which helps robots know where a human is headed or what a human is attempting to do. And in wearable robotics, faculty optimize the control of exoskeletons and prostheses based on individual user preference, but also predict movements to enhance performance.

This work ensures that the robots can interact successfully and safely with humans, and positively impact society.