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David A. Abbink

7 accepted papers

2026

Enabling Embodied Human-Robot Co-Learning: Requirements, Method, and Test with Handover Task

Emma M. van Zoelen, Hugo Veldman-Loopik, Karel van den Bosch, Mark Neerincx, David A. Abbink, Luka Peternel
ICRA 2026poster

Despite a large body of research on robot learning, it has not yet been thoroughly studied how collaborating humans and robots learn reciprocally. In such situations, both humans and robots continuously learn about each other and the task through interaction. This paper addresses the research questi…

Cited by 0Source ↗Scholar ↗
2026

Fitts' List Revisited: An Empirical Study on Function Allocation in a Two-Agent Physical Human-Robot Collaborative Position/Force Task

Nicky Mol, Joseph Micah Prendergast, David A. Abbink, Luka Peternel
RA-L 2026

In this letter, we investigate whether classical function allocation—the principle of assigning tasks to either a human or a machine—holds for physical Human-Robot Collaboration, which is important for providing insights for Industry 5.0 to guide how to best augment rather than replace workers. This

Cited by 2Source ↗Scholar ↗
2026

Fitts' List Revisited: An Empirical Study on Function Allocation in a Two-Agent Physical Human-Robot Collaborative Position/Force Task

Nicky Mol, J. Micah Prendergast, David A. Abbink, Luka Peternel
ICRA 2026poster

In this letter, we investigate whether classical function allocation--the principle of assigning tasks to either a human or a machine--holds for physical Human-Robot Collaboration, which is important for providing insights for Industry 5.0 to guide how to best augment rather than replace workers. Th…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

Enabling Embodied Human-Robot Co-Learning: Requirements, Method, and Test With Handover Task

Emma M. van Zoelen, Hugo Veldman-Loopik, Karel van den Bosch, Mark A. Neerincx, David A. Abbink, Luka Peternel
RA-L 2025

Despite a large body of research on robot learning, it has not yet been thoroughly studied how collaborating humans and robots learn reciprocally. In such situations, both humans and robots continuously learn about each other and the task through interaction. This letter addresses the research quest

Cited by 3Source ↗Scholar ↗
2024

Interactive Multi-Stiffness Mixed Reality Interface: Controlling and Visualizing Robot and Environment Stiffness

Alejandro Díaz Rosales, Jose Rodriguez-Nogueira, Eloise Matheson, David A. Abbink, Luka Peternel
IROS 2024

Teleoperation is a crucial technology enabling human operators to control robots remotely to perform tasks in hazardous and difficult-to-access environments. Tasks in such environments often involve complex physical interactions with tools and objects of various softness. To this end, teleimpedance

Cited by 3Source ↗Scholar ↗
2023

Orbital Head-Mounted Display: A Novel Interface for Viewpoint Control during Robot Teleoperation in Cluttered Environments

Sjoerd Kuitert, Jelle Hofland, Cock J. M. Heemskerk, David A. Abbink, Luka Peternel
IROS 2023poster

Robotic teleoperation is used in various applications, including the nuclear industry, where the experience and intelligence of a human operator are necessary for making complex decisions that are beyond the autonomy of robots. Human-robot interfaces that help strengthen an operators situational awa…

Cited by 2Source ↗Scholar ↗
2022

Foot-operated Tele-impedance Interface for Robot Manipulation Tasks in Interaction with Unpredictable Environments

Stijn Klevering, Winfred Mugge, David A. Abbink, Luka Peternel
IROS 2022poster

Tele-impedance increases interaction performance between a robotic tool and unstructured/unpredictable en-vironments during teleoperation. However, the existing tele-impedance interfaces have several ongoing issues, such as long calibration times and various obstructions for the human operator. In a…

Cited by 5Source ↗Scholar ↗