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20222024
most citedLearning effects in variable autonomy human-robot systems: how much training is enough?

15 citations · 22 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.RO2024

The ATTUNE model for Artificial Trust Towards Human Operators

Giannis Petousakis, Angelo Cangelosi, Rustam Stolkin +1

This paper presents a novel method to quantify Trust in HRI. It proposes an HRI framework for estimating the Robot Trust towards the Human in the context of a narrow and specified…

cs.RO2024

Negotiating Control: Neurosymbolic Variable Autonomy

Georgios Bakirtzis, Manolis Chiou, Andreas Theodorou

Variable autonomy equips a system, such as a robot, with mixed initiatives such that it can adjust its independence level based on the task's complexity and the surrounding environ…

cs.RO202315 cited

Learning effects in variable autonomy human-robot systems: how much training is enough?

Manolis Chiou, Mohammed Talha, Rustam Stolkin

This paper investigates learning effects and human operator training practices in variable autonomy robotic systems. These factors are known to affect performance of a human-robot…

cs.RO2023

A Supervised Machine Learning Approach to Operator Intent Recognition for Teleoperated Mobile Robot Navigation

Evangelos Tsagkournis, Dimitris Panagopoulos, Giannis Petousakis +3

In applications that involve human-robot interaction (HRI), human-robot teaming (HRT), and cooperative human-machine systems, the inference of the human partner's intent is of crit…

cs.RO20234 cited

Robot Health Indicator: A Visual Cue to Improve Level of Autonomy Switching Systems

Aniketh Ramesh, Madeleine Englund, Andreas Theodorou +2

Using different Levels of Autonomy (LoA), a human operator can vary the extent of control they have over a robot's actions. LoAs enable operators to mitigate a robot's performance…

cs.RO20221 cited

Robot Vitals and Robot Health: Towards Systematically Quantifying Runtime Performance Degradation in Robots Under Adverse Conditions

Aniketh Ramesh, Rustam Stolkin, Manolis Chiou

This paper addresses the problem of automatically detecting and quantifying performance degradation in remote mobile robots during task execution. A robot may encounter a variety o…