Object Handovers: a Review for Robotics

TL;DR

This review paper analyzes the current state of human-robot object handovers, focusing on cognitive and physical processes, and proposes standardized metrics for evaluating robotic handover performance.

Contribution

It provides a comprehensive survey of robotic handovers, compares human and robotic behaviors, and introduces a minimal set of evaluation metrics for future research.

Findings

Robotic handovers are analyzed in terms of cognitive and physical processes.

Comparison between human and robotic handover behaviors highlights key areas for improvement.

A minimal set of metrics for evaluating robotic handovers is proposed.

Abstract

This article surveys the literature on human-robot object handovers. A handover is a collaborative joint action where an agent, the giver, gives an object to another agent, the receiver. The physical exchange starts when the receiver first contacts the object held by the giver and ends when the giver fully releases the object to the receiver. However, important cognitive and physical processes begin before the physical exchange, including initiating implicit agreement with respect to the location and timing of the exchange. From this perspective, we structure our review into the two main phases delimited by the aforementioned events: 1) a pre-handover phase, and 2) the physical exchange. We focus our analysis on the two actors (giver and receiver) and report the state of the art of robotic givers (robot-to-human handovers) and the robotic receivers (human-to-robot handovers). We report a comprehensive list of qualitative and quantitative metrics commonly used to assess the interaction. While focusing our review on the cognitive level (e.g., prediction, perception, motion planning, learning) and the physical level (e.g., motion, grasping, grip release) of the handover, we briefly discuss also the concepts of safety, social context, and ergonomics. We compare the behaviours displayed during human-to-human handovers to the state of the art of robotic assistants, and identify the major areas of improvement for robotic assistants to reach performance comparable to human interactions. Finally, we propose a minimal set of metrics that should be used in order to enable a fair comparison among the approaches.