All Outputs (20)

Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments (2023)
Journal Article
Mitchell, D., Emor Baniqued, P. D., Zahid, A., West, A., Nouri Rahmat Abadi, B., Lennox, B., …Jiang, Z. (2023). Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments. IET Cyber-Systems and Robotics, 5(4), Article e12103. https://doi.org/10.1049/csy2.12103

AbstractNuclear facilities have a regulatory requirement to measure radiation levels within Post Operational Clean Out (POCO) around nuclear facilities each year, resulting in a trend towards robotic deployments to gain an improved understanding duri... Read More about Lessons learned: Symbiotic autonomous robot ecosystem for nuclear environments.

Impact of resolution, colour, and motion on object identification in digital twins from robot sensor data (2022)
Journal Article
Bremner, P., & Giuliani, M. (2022). Impact of resolution, colour, and motion on object identification in digital twins from robot sensor data. Frontiers in Robotics and AI, 9, Article 995342. https://doi.org/10.3389/frobt.2022.995342

This paper makes a contribution to research on digital twins that are generated from robot sensor data. We present the results of an online user study in which 240 participants were tasked to identify real-world objects from robot point cloud data. I... Read More about Impact of resolution, colour, and motion on object identification in digital twins from robot sensor data.

Mutual shaping in swarm robotics: User studies in fire and rescue, storage organization, and bridge inspection (2020)
Journal Article
Carrillo-Zapata, D., Milner, E., Hird, J., Tzoumas, G., Vardanega, P. J., Sooriyabandara, M., …Hauert, S. (2020). Mutual shaping in swarm robotics: User studies in fire and rescue, storage organization, and bridge inspection. Frontiers in Robotics and AI, 7, Article 53. https://doi.org/10.3389/frobt.2020.00053

Many real-world applications have been suggested in the swarm robotics literature. However, there is a general lack of understanding of what needs to be done for robot swarms to be useful and trusted by users in reality. This paper aims to investigat... Read More about Mutual shaping in swarm robotics: User studies in fire and rescue, storage organization, and bridge inspection.

User-centred design and evaluation of a tele-operated echocardiography robot (2020)
Journal Article
Giuliani, M., Szczęśniak-Stańczyk, D., Mirnig, N., Stollnberger, G., Szyszko, M., Stańczyk, B., & Tscheligi, M. (2020). User-centred design and evaluation of a tele-operated echocardiography robot. Health and Technology, 10, 649-655. https://doi.org/10.1007/s12553-019-00399-0

We present the collected findings of a user-centred approach for developing a tele-operated robot for remote echocardiography examinations. During the three-year development of the robot, we involved users in all development stages of the robot, to i... Read More about User-centred design and evaluation of a tele-operated echocardiography robot.

A debris clearance robot for extreme environments (2019)
Journal Article
West, C., Giuliani, M., Lennox, B., Cheah, W., Arvin, F., West, A., & Watson, S. (2019). A debris clearance robot for extreme environments. Lecture Notes in Artificial Intelligence, 11649 LNAI, 148-159. https://doi.org/10.1007/978-3-030-23807-0_13

© Springer Nature Switzerland AG 2019. The need for nuclear decommissioning is increasing globally, as power stations and other facilities utilising nuclear reaches the end of their operational life. Currently the majority of decommissioning tasks ar... Read More about A debris clearance robot for extreme environments.

Confidence in uncertainty: Error cost and commitment in early speech hypotheses (2018)
Journal Article
Loth, S., Jettka, K., Giuliani, M., Kopp, S., & de Ruiter, J. (2018). Confidence in uncertainty: Error cost and commitment in early speech hypotheses. PLoS ONE, 13(8), Article e0201516. https://doi.org/10.1371/journal.pone.0201516

© 2018 Loth et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credi... Read More about Confidence in uncertainty: Error cost and commitment in early speech hypotheses.

Towards a cognitive architecture incorporating human feedback for interactive collaborative robots (2018)
Journal Article
Cahya, D. E., & Giuliani, M. (2018). Towards a cognitive architecture incorporating human feedback for interactive collaborative robots. Lecture Notes in Artificial Intelligence, 10965, 486-488. https://doi.org/10.1007/978-3-319-96728-8

The development of new collaborative robotic platforms opens the new possibility of human-robot collaborative scenarios provided that they are controlled by excellent control programs. Interactive collaborative robots need to be autonomous and posses... Read More about Towards a cognitive architecture incorporating human feedback for interactive collaborative robots.

Feature and performance comparison of the V-REP, Gazebo and ARGoS robot simulators (2018)
Journal Article
Pitonakova, L., Giuliani, M., Pipe, A., & Winfield, A. (2018). Feature and performance comparison of the V-REP, Gazebo and ARGoS robot simulators. Lecture Notes in Artificial Intelligence, 10965 LNAI, 357-368. https://doi.org/10.1007/978-3-319-96728-8_30

© Springer International Publishing AG, part of Springer Nature 2018. In this paper, the characteristics and performance of three open-source simulators for robotics, V-REP, Gazebo and ARGoS, are thoroughly analysed and compared. While they all allow... Read More about Feature and performance comparison of the V-REP, Gazebo and ARGoS robot simulators.

Automatically Classifying User Engagement for Dynamic Multi-party Human–Robot Interaction (2017)
Journal Article
Foster, M. E., Gaschler, A., & Giuliani, M. (2017). Automatically Classifying User Engagement for Dynamic Multi-party Human–Robot Interaction. International Journal of Social Robotics, 9(5), 659-674. https://doi.org/10.1007/s12369-017-0414-y

© 2017, The Author(s). A robot agent designed to engage in real-world human–robot joint action must be able to understand the social states of the human users it interacts with in order to behave appropriately. In particular, in a dynamic public spac... Read More about Automatically Classifying User Engagement for Dynamic Multi-party Human–Robot Interaction.

To err is robot: How humans assess and act toward an erroneous social robot (2017)
Journal Article
Mirnig, N., Stollnberger, G., Miksch, M., Stadler, S., Giuliani, M., & Tscheligi, M. (2017). To err is robot: How humans assess and act toward an erroneous social robot. Frontiers in Robotics and AI, 4(MAY), 21. https://doi.org/10.3389/frobt.2017.00021

© 2017 Mirnig, Stollnberger, Miksch, Stadler, Giuliani and Tscheligi. We conducted a user study for which we purposefully programmed faulty behavior into a robot's routine. It was our aim to explore if participants rate the faulty robot different fro... Read More about To err is robot: How humans assess and act toward an erroneous social robot.

Systematic analysis of video data from different human-robot interaction studies: A categorisation of social signals during error situations (2015)
Journal Article
Giuliani, M., Mirnig, N., Stollnberger, G., Stadler, S., Buchner, R., & Tscheligi, M. (2015). Systematic analysis of video data from different human-robot interaction studies: A categorisation of social signals during error situations. Frontiers in Psychology, 6(931), https://doi.org/10.3389/fpsyg.2015.00931

Human–robot interactions are often affected by error situations that are caused by either the robot or the human. Therefore, robots would profit from the ability to recognize when error situations occur. We investigated the verbal and non-verbal soci... Read More about Systematic analysis of video data from different human-robot interaction studies: A categorisation of social signals during error situations.

Ghost-in-the-Machine reveals human social signals for human-robot interaction (2015)
Journal Article
Loth, S., Jettka, K., Giuliani, M., & De Ruiter, J. P. (2015). Ghost-in-the-Machine reveals human social signals for human-robot interaction. Frontiers in Psychology, 6(NOV), https://doi.org/10.3389/fpsyg.2015.01641

© 2015 Loth, Jettka, Giuliani and de Ruiter. We used a new method called "Ghost-in-the-Machine" (GiM) to investigate social interactions with a robotic bartender taking orders for drinks and serving them. Using the GiM paradigm allowed us to identify... Read More about Ghost-in-the-Machine reveals human social signals for human-robot interaction.

Multi-modality gesture detection and recognition with un-supervision, randomization and discrimination (2015)
Journal Article
Wu, D., Chen, G., Clarke, D., Weikersdorfer, D., Giuliani, M., Gaschler, A., & Knoll, A. (2015). Multi-modality gesture detection and recognition with un-supervision, randomization and discrimination. Lecture Notes in Artificial Intelligence, 8925, 608-622. https://doi.org/10.1007/978-3-319-16178-5_43

© Springer International Publishing Switzerland 2015. We describe in this paper our gesture detection and recognition system for the 2014 ChaLearn Looking at People (Track 3: Gesture Recognition) organized by ChaLearn in conjunction with the ECCV 201... Read More about Multi-modality gesture detection and recognition with un-supervision, randomization and discrimination.

Combining unsupervised learning and discrimination for 3D action recognition (2014)
Journal Article
Chen, G., Clarke, D., Giuliani, M., Gaschler, A., & Knoll, A. (2015). Combining unsupervised learning and discrimination for 3D action recognition. Signal Processing, 110, 67-81. https://doi.org/10.1016/j.sigpro.2014.08.024

© 2014 Elsevier B.V. Previous work on 3D action recognition has focused on using hand-designed features, either from depth videos or 2D videos. In this work, we present an effective way to combine unsupervised feature learning with discriminative fea... Read More about Combining unsupervised learning and discrimination for 3D action recognition.

Task-based evaluation of context-sensitive referring expressions in human–robot dialogue (2014)
Journal Article
Foster, M. E., Giuliani, M., & Isard, A. (2014). Task-based evaluation of context-sensitive referring expressions in human–robot dialogue. Language Cognition and Neuroscience, 29(8), 1018-1034. https://doi.org/10.1080/01690965.2013.855802

© 2013 Taylor & Francis. The standard referring-expression generation task involves creating stand-alone descriptions intended solely to distinguish a target object from its context. However, when an artificial system refers to objects in the cours... Read More about Task-based evaluation of context-sensitive referring expressions in human–robot dialogue.

Designing and evaluating a social gaze-control system for a humanoid robot (2014)
Journal Article
Zaraki, A., Mazzei, D., Giuliani, M., & De Rossi, D. (2014). Designing and evaluating a social gaze-control system for a humanoid robot. IEEE Transactions on Human-Machine Systems, 44(2), 157-168. https://doi.org/10.1109/THMS.2014.2303083

This paper describes a context-dependent social gaze-control system implemented as part of a humanoid social robot. The system enables the robot to direct its gaze at multiple humans who are interacting with each other and with the robot. The attenti... Read More about Designing and evaluating a social gaze-control system for a humanoid robot.

Action recognition using ensemble weighted multi-instance learning (2014)
Journal Article
Chen, G., Giuliani, M., Clarke, D., Gaschler, A., & Knoll, A. (2014). Action recognition using ensemble weighted multi-instance learning. IEEE International Conference on Robotics and Automation, 4520-4525. https://doi.org/10.1109/ICRA.2014.6907519

© 2014 IEEE. This paper deals with recognizing human actions in depth video data. Current state-of-the-art action recognition methods use hand-designed features, which are difficult to produce and time-consuming to extend to new modalities. In this p... Read More about Action recognition using ensemble weighted multi-instance learning.

Unsupervised learning spatio-temporal features for human activity recognition from RGB-D video data (2013)
Journal Article
Chen, G., Zhang, F., Giuliani, M., Buckl, C., & Knoll, A. (2013). Unsupervised learning spatio-temporal features for human activity recognition from RGB-D video data. Lecture Notes in Artificial Intelligence, 8239 LNAI, 341-350. https://doi.org/10.1007/978-3-319-02675-6_34

Being able to recognize human activities is essential for several applications, including social robotics. The recently developed commodity depth sensors open up newpossibilities of dealingwith this problem. Existing techniques extract hand-tuned fea... Read More about Unsupervised learning spatio-temporal features for human activity recognition from RGB-D video data.

Using Embodied Multimodal Fusion to Perform Supportive and Instructive Robot Roles in Human-Robot Interaction (2013)
Journal Article
Giuliani, M., & Knoll, A. (2013). Using Embodied Multimodal Fusion to Perform Supportive and Instructive Robot Roles in Human-Robot Interaction. International Journal of Social Robotics, 5(3), 345-356. https://doi.org/10.1007/s12369-013-0194-y

We present a robot that is working with humans on a common construction task. In this kind of interaction, it is important that the robot can perform different roles in order to realise an efficient collaboration. For this, we introduce embodied mult... Read More about Using Embodied Multimodal Fusion to Perform Supportive and Instructive Robot Roles in Human-Robot Interaction.

Design principles for safety in human-robot interaction (2010)
Journal Article
Giuliani, M., Lenz, C., Müller, T., Rickert, M., & Knoll, A. (2010). Design principles for safety in human-robot interaction. International Journal of Social Robotics, 2(3), 253-274. https://doi.org/10.1007/s12369-010-0052-0

The interaction of humans and robots has the potential to set new grounds in industrial applications as well as in service robotics because it combines the strengths of humans, such as flexibility and adaptability, and the strengths of robots, such a... Read More about Design principles for safety in human-robot interaction.