How robots deployed in the real world can leverage human interactions — through demonstrations, feedback, and natural signals — to learn and improve their abilities over time.
Summary
When robots operate outside the lab, the environment is unconstrained and unpredictable — and people are everywhere. Rather than treating this as a problem, this line of work turns it into an opportunity: humans in the loop as a resource for learning. This includes learning local navigation recovery policies from non-expert demonstrations (Del Duchetto 2018, Faris 2025), adapting social behaviours from implicit interaction signals (Del Duchetto 2022), and developing tools that enable novice users to program and assess robot social abilities. A key challenge is designing principled methods that work with sparse, noisy, and unstructured human input — not carefully curated datasets.
Videos
Projects
Principles of Learning from UnStructured Human-Robot Interactions (PLUS-HRI), Funded by the UKRI UK-RAS Network Fundamental Research Grant (PI: Francesco Del Duchetto). Link: https://lcas.lincoln.ac.uk/wp/research/projects/plus-hri/
@inproceedings{faris2025modelling,title={Modelling robot navigation recovery policies from non-expert users' demonstrations in-the-wild},author={Faris, Ahmad and Kucukyilmaz, Ayse and Polydoros, Athanasios and Del Duchetto, Francesco},booktitle={2025 International Conference on Robotic Computing and Communication (RoboticCC)},pages={15--22},year={2025},award={Best Paper Award Nominated}}
@article{del2022learning,title={Learning on the Job: Long-Term Behavioural Adaptation in Human-Robot Interactions},author={Del Duchetto, Francesco and Hanheide, Marc},journal={IEEE Robotics and Automation Letters},volume={7},number={3},pages={6934--6941},year={2022},publisher={IEEE},award={Finalist for IROS 2022 Best Paper Award on Cognitive Robotics by KROS}}
Finalist for IROS 2022 Best Paper Award on Cognitive Robotics by KROS
2020
Automatic Assessment and Learning of Robot Social Abilities
Francesco Del Duchetto, Paul Baxter, and Marc Hanheide
In Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, 2020
@inproceedings{del2020automatic,title={Automatic Assessment and Learning of Robot Social Abilities},author={Del Duchetto, Francesco and Baxter, Paul and Hanheide, Marc},booktitle={Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction},pages={561--563},year={2020},}
Abstract visual programming of social robots for novice users
Onis Brown, Laurence Roberts-Elliott, Francesco Del Duchetto, and 2 more authors
In Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, 2020
@inproceedings{brown2020abstract,title={Abstract visual programming of social robots for novice users},author={Brown, Onis and Roberts-Elliott, Laurence and Del Duchetto, Francesco and Hanheide, Marc and Baxter, Paul},booktitle={Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction},pages={154--156},year={2020},}
@article{del2018not,title={Do not make the same mistakes again and again: Learning local recovery policies for navigation from human demonstrations},author={Del Duchetto, Francesco and Kucukyilmaz, Ayse and Iocchi, Luca and Hanheide, Marc},journal={IEEE Robotics and Automation Letters},volume={3},number={4},pages={4084--4091},year={2018},publisher={IEEE},}