RAP Lab leverages lab experiments, biometric tracking, surveys, interviews, and ethnographic fieldwork to capture both qualitative and quantitative dimensions of human-robot interaction. No single method tells the whole story, so we build our research designs around multiple, complementary approaches.
Quantitative depth
Controlled experiments and biometric data give us measurable, repeatable evidence of how people respond to anthropomorphic technologies, from micro-level physiological shifts to broader behavioral patterns like approach and avoidance. These methods allow us to test specific hypotheses under controlled conditions, isolating the effect of a single variable, such as a robot’s voice pitch or response latency, on human trust and comfort.
Qualitative richness
Interviews and ethnographic fieldwork surface the lived experience behind the numbers: how people describe their trust in a robot, the language they use to anthropomorphize a machine, or the discomfort they struggle to articulate in a structured survey. Spending time in the actual settings where people interact with robots, whether a workplace, a home, or a care facility, reveals dynamics that would never emerge in a lab, from how coworkers talk about a robotic colleague to how families integrate a robot into daily routines.
Surveys as a bridge
Between the depth of interviews and the precision of experiments, surveys let us gather structured self-report data at scale, tracking attitudes and perceptions across larger and more diverse populations than lab studies alone could reach. This helps us understand not just how individual participants respond, but how broader demographic and cultural patterns shape attitudes toward humanlike technology.
Why we combine all of it
Numbers alone can miss context, and stories alone can miss scale. By triangulating across methods, we build a fuller, more credible picture of how anthropomorphic design shapes human behavior and wellbeing. When findings from different methods converge, we gain confidence in the result. When they diverge, that tension often points us toward the most interesting and important questions for future research.