Grant number: FT250100459 | Funding period: 2026 - 2030
Active
M Bilal, TS Ratnayake, DA Chacon, N Lipovetzky, D Oetomo, W Johal
2026-06-12
Learning from Demonstration (LfD) allows novice users to teach robots through demonstrations without coding; however, such demonst..
Q Zhou, DA Chacon, J Pan, W Johal
2026-05-08
Teleoperating a robot arm typically requires either positioning its end-effector directly or programming joint movements. The form..
A Balaska, JES Grønbæk, C Zhang, S Schömbs, W Johal
Hybrid videoconferencing often results in conversational dominance by physically present participants, particularly when remote me..
J Zhang, W Johal, J Knibbe
2026-04-13
Tangible interactions involve multiple sensory cues, enabling the accurate perception of object properties, such as size. Research..
S Schömbs, Y Zhang, C Wang, W Johal
When multi-agentic systems are implemented in human-robot interaction, users interact with a single physical robot while multiple ..
R Tabatabaei, V Kostakos, W Johal
In human-robot collaboration, repeated failures are inevitable and can undermine trust and perceptions of robot intelligence. Whil..
M Bilal, DA Chacon, N Lipovetzky, D Oetomo, W Johal
2026-03-16
Learning from Demonstration allows robots to acquire skills from human demonstrations, making them more accessible to a wider rang..
Y Zhang, S Schömbs, X Pan, J Leusmann, S Mongile, M Obaid, W Johal
Recent developments in large language models and multi-agentic systems present both opportunities and challenges for Human-Robot I..
S Schömbs, Y Zhang, J Goncalves, W Johal
2026-01-02
Recent advances in multi-agentic systems (e.g., AutoGen, OpenAI Agents) allow users to interact with a group of specialised AI age..
K Zawieska, M Obaid, W Johal
2025-01-01