Keywords: Human‑Robot-Interaction, Context-Awareness, Last-Mile Delivery Robot, Parcel Handover, Inclusive Design
TL;DR: We propose an AI-driven handover coordinator for delivery robots that personalizes communication during parcel handovers to improve user satisfaction while highlighting critical challenges in privacy, robustness, ethics, and real-time performance.
Abstract: The rapid rise of automated delivery robots promises faster, contact‑free parcel handovers, yet the final interaction between the robot and the end customer remains a fragile touchpoint. Misaligned expectations, unclear instructions, or inappropriate communication can turn a convenient delivery into a source of frustration.
We propose an AI‑driven handover coordinator that ingests dispatch metadata, real‑time environmental conditions (weather, location, traffic), the recipient's historical interaction profile, and live feedback during the handover. By synthesizing these signals, the AI generates a tailored communication strategy, adjusting tone, movement, and content, to maximize the recipient’s satisfaction. At the same time, this raises critical questions about data privacy, robustness, ethical persuasion, and real-time performance that must be addressed for the solution to be viable.
We hope to spark a critical discussion about the possibilities of using AI in this context in order to pave the way for a design space for delivery robots in the long term.
Submission Number: 9
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