The Grasp Strategy of a Robot Passer Influences Performance and Quality of the Robot-Human Object Handover

Valerio Ortenzi; Francesca Cini; Tommaso Pardi; Naresh Marturi; Rustam Stolkin; Peter Corke; Marco Controzzi

doi:10.3389/frobt.2020.542406

The Grasp Strategy of a Robot Passer Influences Performance and Quality of the Robot-Human Object Handover

Valerio Ortenzi^*, Francesca Cini, Tommaso Pardi, Naresh Marturi, Rustam Stolkin, Peter Corke, Marco Controzzi

^*Corresponding author for this work

Metallurgy and Materials

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

Task-aware robotic grasping is critical if robots are to successfully cooperate with humans. The choice of a grasp is multi-faceted; however, the task to perform primes this choice in terms of hand shaping and placement on the object. This grasping strategy is particularly important for a robot companion, as it can potentially hinder the success of the collaboration with humans. In this work, we investigate how different grasping strategies of a robot passer influence the performance and the perceptions of the interaction of a human receiver. Our findings suggest that a grasping strategy that accounts for the subsequent task of the receiver improves substantially the performance of the human receiver in executing the subsequent task. The time to complete the task is reduced by eliminating the need of a post-handover re-adjustment of the object. Furthermore, the human perceptions of the interaction improve when a task-oriented grasping strategy is adopted. The influence of the robotic grasp strategy increases as the constraints induced by the object's affordances become more restrictive. The results of this work can benefit the wider robotics community, with application ranging from industrial to household human-robot interaction for cooperative and collaborative object manipulation.

Original language	English
Article number	542406
Journal	Frontiers in Robotics and AI
Volume	7
DOIs	https://doi.org/10.3389/frobt.2020.542406
Publication status	Published - 19 Oct 2020

Bibliographical note

Funding Information:
VO and MC initiated this work, oversaw, and advised the research. MC, FC, and VO designed the experiments. VO, NM, and TP built the experimental setup. VO, TP, FC, and MC performed the experiments. RS and MC provided the financial support. All authors contributed to the article and approved the submitted version.

Funding Information:
VO, NM, and RS were supported by the UK National Centre for Nuclear Robotics initiative, funded by EPSRC EP/R02572X/1. TP was supported by an NDA Ph.D. bursary. PC was supported by the Australian Research Council Centre of Excellence for Robotic Vision (project number CE140100016). FC and MC were supported by the European Commission under the Horizon 2020 framework program for Research and Innovation (project acronym: APRIL, project number: 870142).

Publisher Copyright:
© Copyright © 2020 Ortenzi, Cini, Pardi, Marturi, Stolkin, Corke and Controzzi.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

human-robot collaboration (HRC)
human-robot interaction (HRI)
object handover
seamless interaction
task-oriented grasping

ASJC Scopus subject areas

Computer Science Applications
Artificial Intelligence

Access to Document

10.3389/frobt.2020.542406

Cite this

@article{4fc0d5f9a6cd487aa8cb0a76d69eda3c,

title = "The Grasp Strategy of a Robot Passer Influences Performance and Quality of the Robot-Human Object Handover",

abstract = "Task-aware robotic grasping is critical if robots are to successfully cooperate with humans. The choice of a grasp is multi-faceted; however, the task to perform primes this choice in terms of hand shaping and placement on the object. This grasping strategy is particularly important for a robot companion, as it can potentially hinder the success of the collaboration with humans. In this work, we investigate how different grasping strategies of a robot passer influence the performance and the perceptions of the interaction of a human receiver. Our findings suggest that a grasping strategy that accounts for the subsequent task of the receiver improves substantially the performance of the human receiver in executing the subsequent task. The time to complete the task is reduced by eliminating the need of a post-handover re-adjustment of the object. Furthermore, the human perceptions of the interaction improve when a task-oriented grasping strategy is adopted. The influence of the robotic grasp strategy increases as the constraints induced by the object's affordances become more restrictive. The results of this work can benefit the wider robotics community, with application ranging from industrial to household human-robot interaction for cooperative and collaborative object manipulation.",

keywords = "human-robot collaboration (HRC), human-robot interaction (HRI), object handover, seamless interaction, task-oriented grasping",

author = "Valerio Ortenzi and Francesca Cini and Tommaso Pardi and Naresh Marturi and Rustam Stolkin and Peter Corke and Marco Controzzi",

note = "Funding Information: VO and MC initiated this work, oversaw, and advised the research. MC, FC, and VO designed the experiments. VO, NM, and TP built the experimental setup. VO, TP, FC, and MC performed the experiments. RS and MC provided the financial support. All authors contributed to the article and approved the submitted version. Funding Information: VO, NM, and RS were supported by the UK National Centre for Nuclear Robotics initiative, funded by EPSRC EP/R02572X/1. TP was supported by an NDA Ph.D. bursary. PC was supported by the Australian Research Council Centre of Excellence for Robotic Vision (project number CE140100016). FC and MC were supported by the European Commission under the Horizon 2020 framework program for Research and Innovation (project acronym: APRIL, project number: 870142). Publisher Copyright: {\textcopyright} Copyright {\textcopyright} 2020 Ortenzi, Cini, Pardi, Marturi, Stolkin, Corke and Controzzi. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",

year = "2020",

month = oct,

day = "19",

doi = "10.3389/frobt.2020.542406",

language = "English",

volume = "7",

journal = "Frontiers in Robotics and AI",

issn = "2296-9144",

publisher = "Frontiers",

}

TY - JOUR

T1 - The Grasp Strategy of a Robot Passer Influences Performance and Quality of the Robot-Human Object Handover

AU - Ortenzi, Valerio

AU - Cini, Francesca

AU - Pardi, Tommaso

AU - Marturi, Naresh

AU - Stolkin, Rustam

AU - Corke, Peter

AU - Controzzi, Marco

N1 - Funding Information: VO and MC initiated this work, oversaw, and advised the research. MC, FC, and VO designed the experiments. VO, NM, and TP built the experimental setup. VO, TP, FC, and MC performed the experiments. RS and MC provided the financial support. All authors contributed to the article and approved the submitted version. Funding Information: VO, NM, and RS were supported by the UK National Centre for Nuclear Robotics initiative, funded by EPSRC EP/R02572X/1. TP was supported by an NDA Ph.D. bursary. PC was supported by the Australian Research Council Centre of Excellence for Robotic Vision (project number CE140100016). FC and MC were supported by the European Commission under the Horizon 2020 framework program for Research and Innovation (project acronym: APRIL, project number: 870142). Publisher Copyright: © Copyright © 2020 Ortenzi, Cini, Pardi, Marturi, Stolkin, Corke and Controzzi. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/10/19

Y1 - 2020/10/19

N2 - Task-aware robotic grasping is critical if robots are to successfully cooperate with humans. The choice of a grasp is multi-faceted; however, the task to perform primes this choice in terms of hand shaping and placement on the object. This grasping strategy is particularly important for a robot companion, as it can potentially hinder the success of the collaboration with humans. In this work, we investigate how different grasping strategies of a robot passer influence the performance and the perceptions of the interaction of a human receiver. Our findings suggest that a grasping strategy that accounts for the subsequent task of the receiver improves substantially the performance of the human receiver in executing the subsequent task. The time to complete the task is reduced by eliminating the need of a post-handover re-adjustment of the object. Furthermore, the human perceptions of the interaction improve when a task-oriented grasping strategy is adopted. The influence of the robotic grasp strategy increases as the constraints induced by the object's affordances become more restrictive. The results of this work can benefit the wider robotics community, with application ranging from industrial to household human-robot interaction for cooperative and collaborative object manipulation.

AB - Task-aware robotic grasping is critical if robots are to successfully cooperate with humans. The choice of a grasp is multi-faceted; however, the task to perform primes this choice in terms of hand shaping and placement on the object. This grasping strategy is particularly important for a robot companion, as it can potentially hinder the success of the collaboration with humans. In this work, we investigate how different grasping strategies of a robot passer influence the performance and the perceptions of the interaction of a human receiver. Our findings suggest that a grasping strategy that accounts for the subsequent task of the receiver improves substantially the performance of the human receiver in executing the subsequent task. The time to complete the task is reduced by eliminating the need of a post-handover re-adjustment of the object. Furthermore, the human perceptions of the interaction improve when a task-oriented grasping strategy is adopted. The influence of the robotic grasp strategy increases as the constraints induced by the object's affordances become more restrictive. The results of this work can benefit the wider robotics community, with application ranging from industrial to household human-robot interaction for cooperative and collaborative object manipulation.

KW - human-robot collaboration (HRC)

KW - human-robot interaction (HRI)

KW - object handover

KW - seamless interaction

KW - task-oriented grasping

UR - http://www.scopus.com/inward/record.url?scp=85094924909&partnerID=8YFLogxK

U2 - 10.3389/frobt.2020.542406

DO - 10.3389/frobt.2020.542406

M3 - Article

AN - SCOPUS:85094924909

SN - 2296-9144

VL - 7

JO - Frontiers in Robotics and AI

JF - Frontiers in Robotics and AI

M1 - 542406

ER -

The Grasp Strategy of a Robot Passer Influences Performance and Quality of the Robot-Human Object Handover

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this