Outputs (11)

Performance metrics outperform physiological indicators in robotic teleoperation workload assessment (2024)
Journal Article
Odoh, G., Landowska, A., Crowe, E. M., Benali, K., Cobb, S., Wilson, M. L., Maior, H. A., & Kucukyilmaz, A. (2024). Performance metrics outperform physiological indicators in robotic teleoperation workload assessment. Scientific Reports, 14(1), Article 30984. https://doi.org/10.1038/s41598-024-82112-4

Robotics holds the potential to streamline the execution of repetitive and dangerous tasks, which are difficult or impossible for a human operator. However, in complex scenarios, such as nuclear waste management or disaster response, full automation... Read More about Performance metrics outperform physiological indicators in robotic teleoperation workload assessment.

An overview of high-resource automatic speech recognition methods and their empirical evaluation in low-resource environments (2024)
Journal Article
Fatehi, K., Torres Torres, M., & Kucukyilmaz, A. (2025). An overview of high-resource automatic speech recognition methods and their empirical evaluation in low-resource environments. Speech Communication, 167, Article 103151. https://doi.org/10.1016/j.specom.2024.103151

Deep learning methods for Automatic Speech Recognition (ASR) often rely on large-scale training datasets, which are typically unavailable in low-resource environments (LREs). This lack of sufficient and representative training data poses a significan... Read More about An overview of high-resource automatic speech recognition methods and their empirical evaluation in low-resource environments.

Robots in Pain, Humans in Play: Soma as a Qualitative Method for Investigating Intelligent Human-Robot Configurations (2024)
Presentation / Conference Contribution
Chamberlain, A., Ngo, V., McGarry, G., Kucukyilmaz, A., Benford, S., & Higgins, A. (2025, February). Robots in Pain, Humans in Play: Soma as a Qualitative Method for Investigating Intelligent Human-Robot Configurations. Presented at Designing for Bodies: Practices, Imaginaries and Discourses, University of Southern Denmark, Kolding

In this piece we start to explore the ways in which we somatise our interaction with robots as a symbiotic system - both as human and robot, and as human-robot. We also consider the ways that we might want to take our physical nature (existence), for... Read More about Robots in Pain, Humans in Play: Soma as a Qualitative Method for Investigating Intelligent Human-Robot Configurations.

Understanding user needs of personalisation-based automated systems with development and application of novel ideation cards (2024)
Presentation / Conference Contribution
Duvnjak, J., Kucukyilmaz, A., & Houghton, R. (2024, July). Understanding user needs of personalisation-based automated systems with development and application of novel ideation cards. Presented at 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024), Nice, France

Personalisation is a commonly utilised technology in socially focused online platforms. It has gathered widespread usage through its ability to match a system to the needs of users through their data. This allows systems to be more user-friendly or e... Read More about Understanding user needs of personalisation-based automated systems with development and application of novel ideation cards.

TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals (2023)
Presentation / Conference Contribution
Schneiders, E., Chamberlain, A., Fischer, J. E., Benford, S., Castle-Green, S., Ngo, V., Kucukyilmaz, A., Barnard, P., Row Farr, J., Adams, M., Tandavanitj, N., Devlin, K., Mancini, C., & Mills, D. (2023, July). TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals. Presented at First International Symposium on Trustworthy Autonomous Systems (TAS 23), Edinburgh, UK

Cat Royale is an artist-led exploration of trustworthy autonomous systems (TAS) created by the TAS Hub's creative ambassadors Blast Theory. A small community of cats inhabits a purpose built 'cat utopia' at the centre of which a robot arm tries to en... Read More about TAS for Cats: An Artist-led Exploration of Trustworthy Autonomous Systems for Companion Animals.

Somabotics Toolkit for Rapid Prototyping Human-Robot Interaction Experiences using Wearable Haptics (2023)
Presentation / Conference Contribution
Zhou, F., Price, D., Pacchierotti, C., & Kucukyilmaz, A. (2023, July). Somabotics Toolkit for Rapid Prototyping Human-Robot Interaction Experiences using Wearable Haptics. Poster presented at IEEE World Haptics Conference, Delft, Netherlands

This work-in-progress paper presents a prototyping toolkit developed to design haptic interaction experiences. With developments in wearable and sensor technologies, new opportunities arise everyday to create rich haptic interaction experiences actin... Read More about Somabotics Toolkit for Rapid Prototyping Human-Robot Interaction Experiences using Wearable Haptics.

Resolving conflicts during human-robot co-manipulation (2023)
Presentation / Conference Contribution
Al-Saadi, Z., Hamad, Y. M., Aydin, Y., Kucukyilmaz, A., & Basdogan, C. (2023, March). Resolving conflicts during human-robot co-manipulation. Presented at ACM/IEEE International Conference on Human-Robot Interaction, Stockholm, Sweden

This paper proposes a machine learning (ML) approach to detect and resolve motion conflicts that occur between a human and a proactive robot during the execution of a physically collaborative task. We train a random forest classifier to distinguish b... Read More about Resolving conflicts during human-robot co-manipulation.

ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments (2022)
Presentation / Conference Contribution
Fatehi, K., Torres, M. T., & Kucukyilmaz, A. (2022, September). ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments. Presented at Interspeech 2022, Incheon, Korea

Recent improvements in Automatic Speech Recognition (ASR) systems obtain extraordinary results. However, there are specific domains where training data can be either limited or not representative enough, which are known as Low-Resource Environments (... Read More about ScoutWav: Two-Step Fine-Tuning on Self-Supervised Automatic Speech Recognition for Low-Resource Environments.

Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning (2022)
Presentation / Conference Contribution
Serhan, B., Pandya, H., Kucukyilmaz, A., & Neumann, G. (2022, May). Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning. Presented at 2022 IEEE International Conference on Robotics and Automation (ICRA 2022), Philadelphia, USA

Efficient robotic manipulation of objects for sorting and searching often rely upon how well the objects are perceived and the available grasp poses. The challenge arises when the objects are irregular, have similar visual features (e.g., textureless... Read More about Push-to-See: Learning Non-Prehensile Manipulation to Enhance Instance Segmentation via Deep Q-Learning.

Patient, carer, and staff perceptions of robotics in motor rehabilitation: a systematic review and qualitative meta-synthesis (2021)
Journal Article
Laparidou, D., Curtis, F., Akanuwe, J., Goher, K., Niroshan Siriwardena, A., & Kucukyilmaz, A. (2021). Patient, carer, and staff perceptions of robotics in motor rehabilitation: a systematic review and qualitative meta-synthesis. Journal of NeuroEngineering and Rehabilitation, 18(1), Article 181. https://doi.org/10.1186/s12984-021-00976-3

Background: In recent years, robotic rehabilitation devices have often been used for motor training. However, to date, no systematic reviews of qualitative studies exploring the end-user experiences of robotic devices in motor rehabilitation have bee... Read More about Patient, carer, and staff perceptions of robotics in motor rehabilitation: a systematic review and qualitative meta-synthesis.

Intelligent control of exoskeletons through a novel learning-from-demonstration method (2020)
Presentation / Conference Contribution
Ugur, E., Samur, E., Ugurlu, B., Erol Barkana, D., Kucukyilmaz, A., & Bebek, O. (2020, September). Intelligent control of exoskeletons through a novel learning-from-demonstration method. Poster presented at Cybathlon Symposium 2020, Zurich, Switzerland

We present a novel concept that enables the intelligent and adaptive control of exoskeletons through exploiting our state-of-the-art learning from demonstration (LfD) method, namely Conditional Neural Movement Primitives (CNMPs) [1], on our integrate... Read More about Intelligent control of exoskeletons through a novel learning-from-demonstration method.