Nonvisual Human–Robot Handovers: Multimodal Design and Evaluation

Abstract

Human-robot object handovers are especially challenging when visual attention is unavailable or vision cannot be used, such as in low-light, occluded, or visually demanding collaborative tasks. We present a two-cycle, user-centered study of nonvisual handovers. Cycle 1 (Wizard-of-Oz) compared six concepts (user-passive, voice, guiding arm, beeping, haptic, wind): participants preferred autonomy-preserving designs with clear, multisensory spatial cues. Results show that wind and concise voice ranked highest, while beeping and haptics underperformed as standalone channels. We found that physical guidance felt efficient yet autonomy-limiting, while concise voice improved anticipation but added duration. In Cycle 2, we implemented two finalists on a Pepper robot: (i) robot-passive and user-active with airflow (“wind”) and optional speech, and (ii) robot-active and user-passive with autonomous reaching and speech. With 15 participants (within-subject design), wind was faster and more reliable. However, trust, satisfaction, competence, and comfort did not differ.