Left to right: A robot assisting a novice user, exploring teaching tools, and engaging in interactive learning scenarios.
Project Description
Robots are envisioned to assist in diverse home and social contexts, such as helping elderly individuals with daily tasks. This project focuses on enabling robots to adapt to their environments by learning context-specific tasks from human trainers, even those without programming expertise.
Inspired by educational theories, the project explores how robots can better learn from novice users while minimizing human workload. Key challenges include:
Training humans to be effective trainers.
Reducing user disengagement during repetitive teaching tasks.
Leveraging gamification and instructional design for improved engagement and learning outcomes.
This three-year project, funded by the Australian Research Council, began in mid-2021.
Recent Progress
The project has achieved significant milestones, as reflected in the following publications:
Beyond Success: Quantifying Demonstration Quality in Learning from Demonstration(Bilal et al., 2024)
Muhammad Bilal, Nir Lipovetzky, Denny Oetomo, Wafa Johal
2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
Mr.LfD: A Mixed Reality Interface for Robot Learning from Demonstration(Chen et al., 2024)
Jiahao Chen, Antony Chacon, Muhammad Bilal, Qiushi Zhou, Wafa Johal
36th Australian Conference on Human-Computer Interaction (OzCHI ‘24), November 30–December 4, 2024, Brisbane, Australia
Improving Robot Learning from Demonstration via Competitive Interactions and User Interface Interventions(Phaijit et al., 2024)
Ornnalin Phaijit, Claude Sammut, Wafa Johal
2024 Australasian Conference on Robotics and Automation (ACRA 2024)
User Interface Interventions for Improving Robot Learning from Demonstration(Phaijit et al., 2023)
Ornnalin Phaijit, Claude Sammut, Wafa Johal
11th International Conference on Human-Agent Interaction (HAI), 2023
Let’s Compete! The Influence of Human-Agent Competition and Collaboration on Agent Learning and Human Perception(Phaijit et al., 2022)
Ornnalin Phaijit, Claude Sammut, Wafa Johal
10th International Conference on Human-Agent Interaction (HAI), 2022
A Taxonomy of Functional Augmented Reality for Human-Robot Interaction(Phaijit et al., 2022)
Ornnalin Phaijit, Mohammad Obaid, Claude Sammut, Wafa Johal
17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), 2022
Team Members
This project involves contributions from several dedicated researchers, including PhD students:
Ornnalin Phaijit
Muhammad Bilal
References
2024
Beyond Success: Quantifying Demonstration Quality in Learning from Demonstration
Muhammad Bilal , Nir Lipovetzky , Denny Oetomo , and Wafa Johal
In 2024 IEEE/RSJ International conference on Intelligent Robots and Systems (IROS) , 2024
@inproceedings{bilal2024,title={Beyond Success: Quantifying Demonstration Quality in Learning from Demonstration},author={Bilal, Muhammad and Lipovetzky, Nir and Oetomo, Denny and Johal, Wafa},booktitle={2024 IEEE/RSJ International conference on Intelligent Robots and Systems (IROS)},organization={IEEE},year={2024}}
Mr.LfD: A Mixed Reality Interface for Robot Learning from Demonstration
Jiahao Chen , Antony Chacon , Muhammad Bilal , Qiushi Zhou , and Wafa Johal
In Proceedings of the 36th Australian Conference on Human-Computer Interaction (OzCHI ’24), November 30–December 4, 2024, Brisbane, Australia , 2024
@inproceedings{chen2024,title={Mr.LfD: A Mixed Reality Interface for Robot Learning from Demonstration},author={Chen, Jiahao and Chacon, Antony and Bilal, Muhammad and Zhou, Qiushi and Johal, Wafa},booktitle={Proceedings of the 36th Australian Conference on Human-Computer Interaction (OzCHI '24), November 30--December 4, 2024, Brisbane, Australia},organization={ACM},year={2024}}
Improving Robot Learning from Demonstration via Competitive Interactions and User Interface Interventions
Ornnalin Phaijit , Claude Sammut , and Wafa Johal
In 2024 Australasian Conference on Robotics and Automation (ACRA 2024) , 2024
@inproceedings{phaijit2024,title={Improving Robot Learning from Demonstration via Competitive Interactions and User Interface Interventions},author={Phaijit, Ornnalin and Sammut, Claude and Johal, Wafa},booktitle={2024 Australasian Conference on Robotics and Automation (ACRA 2024)},year={2024}}
2023
User Interface Interventions for Improving Robot Learning from Demonstration
Ornnalin Phaijit , Claude Sammut , and Wafa Johal
In Proceedings of the 11th International Conference on Human-Agent Interaction , 2023
@inproceedings{phaijit2023user,title={User Interface Interventions for Improving Robot Learning from Demonstration},author={Phaijit, Ornnalin and Sammut, Claude and Johal, Wafa},booktitle={Proceedings of the 11th International Conference on Human-Agent Interaction},pages={152--161},year={2023},}
2022
Let’s Compete! The Influence of Human-Agent Competition and Collaboration on Agent Learning and Human Perception
Ornnalin Phaijit , Claude Sammut , and Wafa Johal
In Proceedings of the 10th International Conference on Human-Agent Interaction , 2022
@inproceedings{phaijit2022let,title={Let’s Compete! The Influence of Human-Agent Competition and Collaboration on Agent Learning and Human Perception},author={Phaijit, Ornnalin and Sammut, Claude and Johal, Wafa},booktitle={Proceedings of the 10th International Conference on Human-Agent Interaction},pages={86--94},year={2022}}
A Taxonomy of Functional Augmented Reality for Human-Robot Interaction
Ornnalin Phaijit , Mohammad Obaid , Claude Sammut , and Wafa Johal
In 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI) , 2022
@inproceedings{phaijit2022taxonomy,title={A Taxonomy of Functional Augmented Reality for Human-Robot Interaction},author={Phaijit, Ornnalin and Obaid, Mohammad and Sammut, Claude and Johal, Wafa},booktitle={2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI)},pages={294--303},year={2022},organization={IEEE}}
