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 title = {Seeing eye to eye: trustworthy embodiment for task-based conversational agents},
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 year = {2023},
 volume = {10},
 publisher = {Frontiers Media SA},
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 author = {Robb, David A and Lopes, José and Ahmad, Muneeb I and McKenna, Peter E and Liu, Xingkun and Lohan, Katrin and Hastie, Helen},
 journal = {Frontiers in Robotics and AI}
}

@article{
 title = {A Meta-analysis of Vulnerability and Trust in Human-Robot Interaction.},
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 author = {McKenna, P. and Ahmad, M. and Maisva, T. and Nesset, B. and Lohan, K. and Hastie, H.},
 journal = {Transactions on Human-Robot Interaction},
 keywords = {in press}
}

@inproceedings{
 title = {Iterative Development of a Service Robot for Laundry Transport in Nursing Homes ⋆},
 type = {inproceedings},
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 editor = {Springer, undefined},
 booktitle = {International Conference on Social Robotics ( ICSR2022)}
}

@article{
 title = {Building Affordance Relations for Robotic Agents-A Review},
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 author = {Ardón, Paola and Pairet, Èric and Lohan, Katrin S. and Ramamoorthy, Subramanian and Petrick, Ronald},
 journal = {arXiv preprint arXiv:2105.06706}
}

@inproceedings{
 title = {Real-Time Adaptive Game to Reduce Cognitive Load},
 type = {inproceedings},
 year = {2021},
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 author = {Hennings, Calum and Ahmad, Muneeb and Lohan, Katrin S.},
 booktitle = {Proceedings of the 9th International Conference on Human-Agent Interaction}
}

@article{
 title = {Affordance-Aware Handovers with Human Arm Mobility Constraints},
 type = {article},
 year = {2021},
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 author = {Ardón, Paola and Cabrera, Maria Eugenia and Pairet, Èric and Petrick, Ron and Ramamoorthy, Subramanian and Lohan, Katrin S. and Cakmak, Maya},
 journal = {IEEE Robotics and Automation Letters (RA-L)}
}

@article{
 title = {Autonomous Rollator: A Case Study in the Agebots Project},
 type = {article},
 year = {2021},
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 author = {Frei, Jonas and Havelka, Anina and Wüst, Markus and Nielsen, Einar and Ziltener, Andreas and Lohan, Katrin S.},
 journal = {arXiv preprint arXiv:2108.13648}
}

@inproceedings{
 title = {"Hey robot, where is my drink?" : Project agebots: multidisciplinary perspectives on service robotics in the field of elderly care},
 type = {inproceedings},
 year = {2021},
 websites = {https://nbn-resolving.org/urn:nbn:de:bsz:946-opus4-62920},
 city = {Frankfurt am Main},
 institution = {Frankfurt University of Applied Sciences},
 series = {Connected Living : international and interdisciplinary conference (2021), Frankfurt am Main},
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 citation_key = {HavelkaDeGiorgiFreietal.2021},
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 abstract = {Service robotics offers great potential for retirement and nursing homes. In the present project Agebots (Implementation of service robotics in the field of elderly care), founded by the Swiss Innovation Agency (Innosuisse), a multidisciplinary team is investigating and testing the implementation of service robotics in elderly care. The pursued dimensions are human, technology, business, and law. The project is carried out in cooperation with two implementation partners: a retirement and nursing home and a robot manufacturer, both based in Switzerland. The project is still ongoing and will be completed by 2022. So far, the use of robots in elderly care has proven to be challenging regarding all different dimensions. These challenges have yet to be overcome to ensure a safe implementation that adds value for both caregivers and the elderly and efficiently supports the operations at the retirement and nursing home. The human centered and iterative approach of the present project allows an early identification of potential challenges and the end-users’ needs. This way, the challenges can be addressed proactively, prior to the implementation in the retirement and nursing home.},
 bibtype = {inproceedings},
 author = {Havelka, Anina and Giorgi, Nadine De and Frei, Jonas and Früh, Alfred and Lehmann, Stephanie and Lohan, Katrin S. and Lohmann, Melinda F and Misoch, Sabina and Nielsen, Einar and Reinhardt, Michèle and Ruf, Esther and Wüst, Markus and Ziegler, Michael and Ziltener, Andreas},
 doi = {10.48718/zwes-7n19},
 booktitle = {Connected Living: international and interdisciplinary conference (2021), Frankfurt am Main}
}

Service robotics offers great potential for retirement and nursing homes. In the present project Agebots (Implementation of service robotics in the field of elderly care), founded by the Swiss Innovation Agency (Innosuisse), a multidisciplinary team is investigating and testing the implementation of service robotics in elderly care. The pursued dimensions are human, technology, business, and law. The project is carried out in cooperation with two implementation partners: a retirement and nursing home and a robot manufacturer, both based in Switzerland. The project is still ongoing and will be completed by 2022. So far, the use of robots in elderly care has proven to be challenging regarding all different dimensions. These challenges have yet to be overcome to ensure a safe implementation that adds value for both caregivers and the elderly and efficiently supports the operations at the retirement and nursing home. The human centered and iterative approach of the present project allows an early identification of potential challenges and the end-users’ needs. This way, the challenges can be addressed proactively, prior to the implementation in the retirement and nursing home.

@inproceedings{
 title = {Social Robot for STEM Education},
 type = {inproceedings},
 year = {2020},
 websites = {https://dl.acm.org/doi/abs/10.1145/3371382.3378291?casa_token=mtX5HPFSqhEAAAAA:zGtvouSVxsEhqwg_XMV_3UL__h80H3JTpX0wojlp9rguIwjF4L1FVrdB4nqS9gQml7HPKoNHRyRI_m0},
 publisher = {ACM},
 id = {3107e9af-e51f-3d06-bcf4-734054a733a6},
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 citation_key = {Ahmad2020b},
 source_type = {inproceedings},
 private_publication = {false},
 abstract = {This work explores the use of the Cozmo robot to deliver mathematicseducation. Recently, we see a lot of work presented onusing robots for education but few works centred around the agegroup of children between 14-17 years of age in combination witha non-humanoid robot. Reflecting on this limitation, Cozmo autonomouslydelivered engaging material and exercises to learners.We studied the subjective ratings of young learners' knowledgegains with Cozmo on the topics of algebra, geometry and trigonometry.We found that participants' subjective rating on their knowledgechanged significantly after the interaction. This implied apositive influence of employing Cozmo with this age group andalso reflected on the need to do more research in schools withaffordable non-humanoid, autonomous social robots.},
 bibtype = {inproceedings},
 author = {Ahmad, Muneeb and Khordi-moodi, Mark and Lohan, Katrin Solveig},
 doi = {10.1145/3371382.3378291},
 booktitle = {15th Annual ACM/IEEE International Conference on Human Robot Interaction}
}

This work explores the use of the Cozmo robot to deliver mathematicseducation. Recently, we see a lot of work presented onusing robots for education but few works centred around the agegroup of children between 14-17 years of age in combination witha non-humanoid robot. Reflecting on this limitation, Cozmo autonomouslydelivered engaging material and exercises to learners.We studied the subjective ratings of young learners' knowledgegains with Cozmo on the topics of algebra, geometry and trigonometry.We found that participants' subjective rating on their knowledgechanged significantly after the interaction. This implied apositive influence of employing Cozmo with this age group andalso reflected on the need to do more research in schools withaffordable non-humanoid, autonomous social robots.

@article{
 title = {A framework to estimate cognitive load using physiological data},
 type = {article},
 year = {2020},
 keywords = {Cognitive load,Framework,Human-computer interaction,Physiological data},
 id = {8a30f3a0-e61e-3ef6-8107-0de3c1353440},
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 citation_key = {Ahmad2020c},
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 abstract = {Cognitive load has been widely studied to help understand human performance. It is desirable to monitor user cognitive load in applications such as automation, robotics, and aerospace to achieve operational safety and to improve user experience. This can allow efficient workload management and can help to avoid or to reduce human error. However, tracking cognitive load in real time with high accuracy remains a challenge. Hence, we propose a framework to detect cognitive load by non-intrusively measuring physiological data from the eyes and heart. We exemplify and evaluate the framework where participants engage in a task that induces different levels of cognitive load. The framework uses a set of classifiers to accurately predict low, medium and high levels of cognitive load. The classifiers achieve high predictive accuracy. In particular, Random Forest and Naive Bayes performed best with accuracies of 91.66% and 85.83% respectively. Furthermore, we found that, while mean pupil diameter change for both right and left eye were the most prominent features, blinking rate also made a moderately important contribution to this highly accurate prediction of low, medium and high cognitive load. The existing results on accuracy considerably outperform prior approaches and demonstrate the applicability of our framework to detect cognitive load.},
 bibtype = {article},
 author = {Ahmad, Muneeb Imtiaz and Keller, Ingo and Robb, David A and Lohan, Katrin S},
 doi = {10.1007/s00779-020-01455-7},
 journal = {Personal and Ubiquitous Computing}
}

Cognitive load has been widely studied to help understand human performance. It is desirable to monitor user cognitive load in applications such as automation, robotics, and aerospace to achieve operational safety and to improve user experience. This can allow efficient workload management and can help to avoid or to reduce human error. However, tracking cognitive load in real time with high accuracy remains a challenge. Hence, we propose a framework to detect cognitive load by non-intrusively measuring physiological data from the eyes and heart. We exemplify and evaluate the framework where participants engage in a task that induces different levels of cognitive load. The framework uses a set of classifiers to accurately predict low, medium and high levels of cognitive load. The classifiers achieve high predictive accuracy. In particular, Random Forest and Naive Bayes performed best with accuracies of 91.66% and 85.83% respectively. Furthermore, we found that, while mean pupil diameter change for both right and left eye were the most prominent features, blinking rate also made a moderately important contribution to this highly accurate prediction of low, medium and high cognitive load. The existing results on accuracy considerably outperform prior approaches and demonstrate the applicability of our framework to detect cognitive load.

@inproceedings{
 title = {Robots in the Danger Zone: Exploring Public Perception through Engagement},
 type = {inproceedings},
 year = {2020},
 websites = {https://dl.acm.org/doi/abs/10.1145/3319502.3374789?casa_token=y1VbWQxbE-kAAAAA:FjcegWHe7SzN-Rg2YKqYXsXO3LZDG2rTlHRfDqtdI8nerenvSubfNkheTlfxFIC6DGfGBmCuZyKi8fk},
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 citation_key = {Robb2020},
 source_type = {conference},
 notes = {15th Annual ACM/IEEE International Conference on Human-Robot Interaction 2020, HRI 2020 ; Conference date: 23-03-2020 Through 26-03-2020},
 private_publication = {false},
 abstract = {Public perceptions of Robotics and Artificial Intelligence (RAI) are important in the acceptance, uptake, government regulation and research funding of this technology. Recent research has shown that the public's understanding of RAI can be negative or inaccurate. We believe effective public engagement can help ensure that public opinion is better informed. In this paper, we describe our first iteration of a high throughput in-person public engagement activity. We describe the use of a light touch quiz-format survey instrument to integrate in-the-wild research participation into the engagement, allowing us to probe both the effectiveness of our engagement strategy, and public perceptions of the future roles of robots and humans working in dangerous settings, such as in the off-shore energy sector. We critique our methods and share interesting results into generational differences within the public's view of the future of Robotics and AI in hazardous environments. These findings include that older peoples' views about the future of robots in hazardous environments were not swayed by exposure to our exhibit, while the views of younger people were affected by our exhibit, leading us to consider carefully in future how to more effectively engage with and inform older people.},
 bibtype = {inproceedings},
 author = {Robb, David and Ahmad, Muneeb and Tiseo, Carlo and Aracri, Simona and McConnell, Alistair Campbell and Page, Vincent and Dondrup, Christian and Garcia, Francisco Javier Chiyah and Nguyen, Hai-Nguyen and Pairet Artau, Èric and Ardon, Paola and Semwal, Tushar and Taylor, Hazel and Wilson, Lindsay and Lane, David Michael and Hastie, Helen and Lohan, Katrin Solveig},
 doi = {10.1145/3319502.3374789},
 booktitle = {15th Annual ACM/IEEE International Conference on Human Robot Interaction}
}

Public perceptions of Robotics and Artificial Intelligence (RAI) are important in the acceptance, uptake, government regulation and research funding of this technology. Recent research has shown that the public's understanding of RAI can be negative or inaccurate. We believe effective public engagement can help ensure that public opinion is better informed. In this paper, we describe our first iteration of a high throughput in-person public engagement activity. We describe the use of a light touch quiz-format survey instrument to integrate in-the-wild research participation into the engagement, allowing us to probe both the effectiveness of our engagement strategy, and public perceptions of the future roles of robots and humans working in dangerous settings, such as in the off-shore energy sector. We critique our methods and share interesting results into generational differences within the public's view of the future of Robotics and AI in hazardous environments. These findings include that older peoples' views about the future of robots in hazardous environments were not swayed by exposure to our exhibit, while the views of younger people were affected by our exhibit, leading us to consider carefully in future how to more effectively engage with and inform older people.

@article{
 title = {Affordances in Robotic Tasks - A Survey},
 type = {article},
 year = {2020},
 volume = {abs/2004.0},
 websites = {https://arxiv.org/abs/2004.07400},
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 author = {Ardón, Paola and Pairet, Èric and Lohan, Katrin S and Ramamoorthy, Subramanian and Petrick, Ronald P A},
 journal = {CoRR}
}

@inproceedings{
 title = {Self-Assessment of Grasp Affordance Transfer},
 type = {inproceedings},
 year = {2020},
 websites = {https://arxiv.org/abs/2007.02132},
 id = {cb1f05af-d853-39a6-8d5f-c3babaf218b4},
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 author = {Ardón, Paola and Pairet, Èric and Petrick, Ron and Ramamoorthy, Subramanian and Lohan, Katrin Solveig},
 booktitle = {2020 IEEE/RSJ International Conference on Intelligent Robots and Systems}
}

@article{
 title = {On the Illumination Influence for Object Learning on Robot Companions},
 type = {article},
 year = {2020},
 keywords = {data augmentation,human-robot interaction,long-term engagement,object learning,visual perception},
 pages = {154},
 websites = {https://doi.org/10.3389/frobt.2019.00154},
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 bibtype = {article},
 author = {Keller, Ingo and Lohan, Katrin S},
 journal = {Frontiers in Robotics and AI},
 number = {6}
}

@inproceedings{
 title = {Towards a Multimodal Measure for Physiological Behaviours to Estimate Cognitive Load.},
 type = {inproceedings},
 year = {2020},
 websites = {https://link.springer.com/chapter/10.1007/978-3-030-49044-7_1},
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 author = {Ahmad, Muneeb Imtiaz and Robb, David A and Keller, Ingo and Lohan, Katrin S},
 doi = {10.1007/978-3-030-49044-7_1},
 booktitle = {HCI International 2020}
}

@inproceedings{
 title = {Multimodal Representation Learning for Human Robot Interaction},
 type = {inproceedings},
 year = {2020},
 websites = {https://dl.acm.org/doi/abs/10.1145/3371382.3378265?casa_token=hu3mgTrU9foAAAAA:A8r_DZ_ei4USRepVmqom-WQt2Fkq80EpwZgzk9xI3HEljPF4FKlnQ3ozSAQyllvbIorWx5cgJshvPmw},
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 citation_key = {Sheppard2020},
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 notes = {15th Annual ACM/IEEE International Conference on Human-Robot Interaction 2020, HRI 2020 ; Conference date: 23-03-2020 Through 26-03-2020},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Sheppard, Eli and Lohan, Katrin Solveig},
 doi = {10.1145/3371382.3378265},
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@inbook{
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 author = {Lohan, Katrin Solveig and Ahmad, Muneeb and Dondrup, Christian and Ardon, Paola and Pairet Artau, Èric and Vinciarelli, Alessandro},
 chapter = {Adapting Movements and Behaviour to Favour Communication in Human-Robot Interaction},
 title = {Springer Book on Modelling Human Motion}
}

@article{
 title = {Proceedings of the AI-HRI Symposium at AAAI-FSS 2020},
 type = {article},
 year = {2020},
 volume = {abs/2010.1},
 websites = {https://arxiv.org/abs/2010.13830},
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 journal = {CoRR}
}

@article{
 title = {Learning Grasp Affordance Reasoning Through Semantic Relations},
 type = {article},
 year = {2019},
 pages = {4571-4578},
 volume = {4},
 publisher = {IEEE},
 id = {b9fdb2d0-766c-3aae-b8ae-1c3b333ecc49},
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 abstract = {Reasoning about object affordances allows an autonomous agent to perform generalised manipulation tasks among object instances. While current approaches to grasp affordance estimation are effective, they are limited to a single hypothesis. We present an approach for detection and extraction of multiple grasp affordances on an object via visual input. We define semantics as a combination of multiple attributes, which yields benefits in terms of generalisation for grasp affordance prediction. We use Markov Logic Networks to build a knowledge base graph representation to obtain a probability distribution of grasp affordances for an object. To harvest the knowledge base, we collect and make available a novel dataset that relates different semantic attributes. We achieve reliable mappings of the predicted grasp affordances on the object by learning prototypical grasping patches from several examples. We show our method's generalisation capabilities on grasp affordance prediction for novel instances and compare with similar methods in the literature. Moreover, using a robotic platform, on simulated and real scenarios, we evaluate the success of the grasping task when conditioned on the grasp affordance prediction.},
 bibtype = {article},
 author = {Ardon, Paola and Pairet, Èric and Petrick, Ronald P A and Ramamoorthy, Subramanian and Lohan, Katrin Solveig},
 doi = {10.1109/LRA.2019.2933815},
 journal = {IEEE Robotics and Automation Letters},
 number = {4}
}

Reasoning about object affordances allows an autonomous agent to perform generalised manipulation tasks among object instances. While current approaches to grasp affordance estimation are effective, they are limited to a single hypothesis. We present an approach for detection and extraction of multiple grasp affordances on an object via visual input. We define semantics as a combination of multiple attributes, which yields benefits in terms of generalisation for grasp affordance prediction. We use Markov Logic Networks to build a knowledge base graph representation to obtain a probability distribution of grasp affordances for an object. To harvest the knowledge base, we collect and make available a novel dataset that relates different semantic attributes. We achieve reliable mappings of the predicted grasp affordances on the object by learning prototypical grasping patches from several examples. We show our method's generalisation capabilities on grasp affordance prediction for novel instances and compare with similar methods in the literature. Moreover, using a robotic platform, on simulated and real scenarios, we evaluate the success of the grasping task when conditioned on the grasp affordance prediction.

@inproceedings{
 title = {Towards a Conversational Agent for Remote Robot-Human Teaming},
 type = {inproceedings},
 year = {2019},
 keywords = {autonomous systems,conversational agent,remote robots},
 pages = {548-549},
 publisher = {IEEE},
 city = {United States},
 series = {ACM/IEEE International Conference on Human-Robot Interaction (HRI)},
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 abstract = {There are many challenges when it comes to deploying robots remotely including lack of operator situation awareness and decreased trust. Here, we present a conversational agent embodied in a Furhat robot that can help with the deployment of such remote robots by facilitating teaming with varying levels of operator control.},
 bibtype = {inproceedings},
 author = {Lopes, José and Robb, David A and Ahmad, Muneeb and Liu, Xingkun and Lohan, Katrin and Hastie, Helen},
 doi = {10.1109/HRI.2019.8673286},
 booktitle = {2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)}
}

There are many challenges when it comes to deploying robots remotely including lack of operator situation awareness and decreased trust. Here, we present a conversational agent embodied in a Furhat robot that can help with the deployment of such remote robots by facilitating teaming with varying levels of operator control.

@inproceedings{
 title = {Introducing a Scalable and Modular Control Framework for Low-cost Monocular Robots in Hazardous Environments},
 type = {inproceedings},
 year = {2019},
 pages = {6421--6426},
 websites = {https://www.iros2019.org/},
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 private_publication = {false},
 bibtype = {inproceedings},
 author = {Taylor, Hazel M and Dondrup, Christian and Lohan, Katrin Solveig},
 booktitle = {2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}
}

@inproceedings{
 title = {A Digital Twin for Human-Robot Interaction},
 type = {inproceedings},
 year = {2019},
 pages = {372},
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 author = {Pairet, Èric and Ardón, Paola and Liu, Xingkun and Lopes, José and Hastie, Helen and Lohan, Katrin S},
 booktitle = {2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)}
}

@inproceedings{
 title = {Integrated real-time, non-intrusive Measurements for Mental Load},
 type = {inproceedings},
 year = {2019},
 id = {bc1a8686-21b3-32d1-a8c8-065cedfd0bbd},
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 bibtype = {inproceedings},
 author = {Ahmad, Muneeb and Keller, Ingo and Lohan, Katrin},
 booktitle = {CHI 2019 Workshop: "Everyday Automation Experience: Non-Expert Users Encountering Ubiquitous Automated Systems"}
}

@article{
 title = {Trust and Cognitive Load During Human-Robot Interaction},
 type = {article},
 year = {2019},
 id = {43547bdd-1ae5-36c5-b0ac-e58a5a8dae53},
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 author = {Ahmad, Muneeb Imtiaz and Bernotat, Jasmin and Lohan, Katrin and Eyssel, Friederike},
 journal = {arXiv preprint arXiv:1909.05160}
}

@article{
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 type = {article},
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}

@inproceedings{
 title = {Exploring Interaction with Remote Autonomous Systems using Conversational Agents},
 type = {inproceedings},
 year = {2019},
 keywords = {Explainable AI,Multimodal interfaces,Natural Language Interfaces,Remote Autonomous Systems,Transparency,Trust},
 publisher = {ACM},
 id = {f6678c33-b756-3952-a5d3-e0371b79fde2},
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 hidden = {false},
 citation_key = {eaa73bdac3274b2fba2423c4b28bb4e8},
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 abstract = {Autonomous vehicles and robots are increasingly being deployed to remote, dangerous environments in the energy sector, search and rescue and the military. As a result, there is a need for humans to interact with these robots to monitor their tasks, such as inspecting and repairing offshore wind-turbines. Conversational Agents can improve situation awareness and transparency, while being a hands-free medium to communicate key information quickly and succinctly. As part of our user-centered design of such systems, we conducted an in-depth immersive qualitative study of twelve marine research scientists and engineers, interacting with a prototype Conversational Agent. Our results expose insights into the appropriate content and style for the natural language interaction and, from this study, we derive nine design recommendations to inform future Conversational Agent design for remote autonomous systems.},
 bibtype = {inproceedings},
 author = {Robb, David A and Lopes, Jose and Padilla, Stefano and Laskov, Atanas and Garcia, Francisco Javier Chiyah and Liu, Xingkun and Scharff Willners, Jonatan and Valeyrie, Nicolas and Lohan, Katrin and Lane, David and Patron, Pedro and Petillot, Yvan and Chantler, Michael John and Hastie, Helen},
 booktitle = {DIS '19: Proceedings of the 2019 Designing Interactive Systems Conference}
}

Autonomous vehicles and robots are increasingly being deployed to remote, dangerous environments in the energy sector, search and rescue and the military. As a result, there is a need for humans to interact with these robots to monitor their tasks, such as inspecting and repairing offshore wind-turbines. Conversational Agents can improve situation awareness and transparency, while being a hands-free medium to communicate key information quickly and succinctly. As part of our user-centered design of such systems, we conducted an in-depth immersive qualitative study of twelve marine research scientists and engineers, interacting with a prototype Conversational Agent. Our results expose insights into the appropriate content and style for the natural language interaction and, from this study, we derive nine design recommendations to inform future Conversational Agent design for remote autonomous systems.

@article{
 title = {Reasoning on Grasp-Action Affordances},
 type = {article},
 year = {2019},
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 author = {Ardón, Paola and Pairet, Èric and Petrick, Ron and Ramamoorthy, Subramanian and Lohan, Katrin},
 journal = {arXiv preprint arXiv:1905.10610}
}

@article{
 title = {Challenges in Collaborative HRI for Remote Robot Teams},
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 author = {Hastie, Helen and Robb, David A and Lopes, José and Ahmad, Muneeb and Bras, Pierre Le and Liu, Xingkun and Petrick, Ronald and Lohan, Katrin and Chantler, Mike J},
 journal = {arXiv preprint arXiv:1905.07379}
}

@inproceedings{
 title = {Multi-Modal Measurements of Mental Load},
 type = {inproceedings},
 year = {2019},
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 author = {Keller, Ingo and Ahmad, Muneeb and Lohan, Katrin},
 booktitle = {CHI 2019 Workshop: "The Challenges of Working on Social Robots that Collaborate with People"}
}

@article{
 title = {Social Impact of recharging activity in long-term HRI and verbal strategies to manage user expectations during recharge},
 type = {article},
 year = {2018},
 volume = {5},
 id = {9db8c3c0-f03e-3d2a-b2ac-1da4f9e8e2fa},
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 abstract = {Social robots perform tasks to help humans in their daily activities. However, if they fail to fulfill expectations this may affect their acceptance. This work investigates the service degradation caused by recharging, during which the robot is socially inactive. We describe two studies conducted in an ecologically valid office environment. In the first long-term study (3 weeks), we investigated the service degradation caused by the recharging behavior of a social robot. In the second study, we explored the social strategies used to manage users’ expectations during recharge. Our findings suggest that the use of verbal strategies (transparency, apology, and politeness) can make robots more acceptable to users during recharge.},
 bibtype = {article},
 author = {Deshmukh, Amol and Lohan, Katrin Solveig and Rajendran, Gnanathusharan and Aylett, Ruth},
 doi = {10.3389/frobt.2018.00023},
 journal = {Frontiers in Robotics and AI}
}

Social robots perform tasks to help humans in their daily activities. However, if they fail to fulfill expectations this may affect their acceptance. This work investigates the service degradation caused by recharging, during which the robot is socially inactive. We describe two studies conducted in an ecologically valid office environment. In the first long-term study (3 weeks), we investigated the service degradation caused by the recharging behavior of a social robot. In the second study, we explored the social strategies used to manage users’ expectations during recharge. Our findings suggest that the use of verbal strategies (transparency, apology, and politeness) can make robots more acceptable to users during recharge.

@inproceedings{
 title = {Symptoms of Cognitive Load in Interactions with a Dialogue System.},
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 year = {2018},
 city = {Boulder, CO, USA},
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@article{
 title = {Proceedings of the AI-HRI Symposium at AAAI-FSS 2018},
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 journal = {CoRR}
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@article{
 title = {Towards improved child robot interaction by understanding eye movements.},
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 author = {Lohan, K S and Sheppard, E and Little, G E and Rajendran, G},
 doi = {10.1109/TCDS.2018.2838342},
 journal = {IEEE Transactions on Cognitive and Developmental Systems}
}

@inproceedings{
 title = {Towards robust grasps: Using the environment semantics for robotic object affordances},
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 author = {Ardon Ramirez, Paola and Pairet Artau, Èric and Ramamoorthy, Subramanian and Lohan, Katrin Solveig},
 booktitle = {AAAI 2018 Fall Symposium: Reasoning and Learning in Real World Systems for Long-term Autonomy}
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@inproceedings{
 title = {Object Affordances by Inferring on the Surroundings},
 type = {inproceedings},
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 bibtype = {inproceedings},
 author = {Ardón, Paola and Ramamoorthy, Subramanian and Lohan, Katrin Solveig},
 booktitle = {Workshop on Advanced Robotics and its Social Impacts (ARSO)}
}

@inproceedings{
 title = {How can we transition from lab to the real world with our HCI and HRI setups?},
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 year = {2018},
 keywords = {Design,Human computer interaction,Performance,Reliability,human robot interaction},
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In this position paper, we present the issues we and others have found when moving from the controlled lab space into the field. We therefore recommend some dos and don'ts for facing the challenge of transferring your research prototype from the lab to the real world. During this transfer, we often encounter crucial disconnects between our envisaged evaluation protocol and real life, often related to differing user expectations outside controlled experimental interactions. The redeployment of complex systems in unfamiliar (and often dissimilar) environments presents additional challenges.In this paper, we present some example transitions in the fields of mobile HCI and HRI. Based on these experiences, we list the possible roadblocks that other researchers might encounter and provide guidelines and suggestions for dealing with frequently encountered issues. We hope that with this paper we can help stimulate the discussion on the pathway to undertaking scientifically reproducible evaluations in the wild.

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@inproceedings{
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We present the UK Robotics and Arti cial Intelligence Hub for O shore Robotics for Certi cation of Assets (ORCA Hub), a 3.5 year EPSRC funded, multi-site project. The ORCA Hub vision is to use teams of robots and autonomous intelligent systems (AIS) to work on o shore energy platforms to enable cheaper, safer and more e cient working practices. The ORCA Hub will research, integrate, validate and deploy remote AIS solutions that can operate with existing and future o shore energy assets and sensors, interacting safely in autonomous or semi-autonomous modes in complex and cluttered environments, co-operating with remote operators. The goal is that through the use of such robotic systems o shore, the need for personnel will decrease. To enable this to happen, the remote operator will need a high level of situation awareness and key to this is the transparency of what the autonomous systems are doing and why. This increased transparency will facilitate a trusting relationship, which is particularly key in high-stakes, hazardous situations.

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@inproceedings{
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