Towards smooth human-robot handover with a vision-based tactile sensor

Rayamane, Prasad ORCID: https://orcid.org/0000-0001-6336-7393, Munguia Galeano, Francisco ORCID: https://orcid.org/0000-0001-8397-3083, Tafrishi, Seyed Amir ORCID: https://orcid.org/0000-0001-9829-3144 and Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902 2023. Towards smooth human-robot handover with a vision-based tactile sensor. Presented at: Annual Conference Towards Autonomous Robotic Systems, 13-15 September 2023. Published in: Iida, F., Maiolino, P., Abdulali, A. and Wang, M. eds. TAROS 2023: Towards Autonomous Robotic Systems. Lecture Notes in Computer Science book series (14136) Cham, Switzerland: Springer, pp. 431-442. 10.1007/978-3-031-43360-3_35

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Abstract

Cooperative human-robot interaction often requires successful handovers of objects between the two entities. However, the assumption that a human can reliably grasp an object from a robot is not always valid. To address this issue, we propose a vision-based tactile sensor for object handover framework that utilises a low-cost sensor with variable sensitivity and pressure. The sensor comprises a latex layer that makes contact with the object and a tracking marker that registers the resulting changes in position. By pre-processing this information, a robot can determine whether it is necessary to open the gripper. Our approach is validated through an exploratory user study involving ten participants who completed handover tasks involving eight objects of varying shapes and stiffness, including rigid and deformable objects like raspberries and dough. The study results demonstrate the effectiveness of our approach, with a success rate of 94%. Additionally, users reported less difficulty performing the handover tasks when the sensitivity value was decreased. Overall, our vision-based tactile sensor framework offers a promising solution for the challenging problem of human-robot handover in cooperative settings.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Publisher:	Springer
ISBN:	978-3-031-43359-7
Date of First Compliant Deposit:	10 July 2023
Date of Acceptance:	6 July 2023
Last Modified:	11 Nov 2024 11:15
URI:	https://orca.cardiff.ac.uk/id/eprint/160929

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