Published in ACM/SIGAPP - Thessaloniki, Greece, 2026
Our findings demonstrate that pre-deployment role and sensing specialization are powerful design considerations for multi-robot systems facing time-conflicting tasks, where varying the degree of behavioral heterogeneity can tune system performance toward either task.
Recommended citation: TBD Paper link here.
Published in ICSR - Odense, Denmark, 2024
Qualitative interviews with participants confirmed that robot proximity was a decisive factor in which robot they preferred to call, and that a robot staying nearby over time made it “part of the team”.
Recommended citation: Webb, N., Milivojevic, S., Sobhani, M., Madin, Z. R., Ward, J. C., Yusuf, S., ... & Hunt, E. R. (2024, October). Co-movement and trust development in human-robot teams. In International Conference on Social Robotics (pp. 107-120). Singapore: Springer Nature Singapore. Paper link here.
Published in TAS - Austin, Texas, 2024
In designing robot systems with swift trust in mind, given the reliance on surface level cues such as robot appearance, it is also important to be aware of how different robot forms can influence expectations of capability.
Recommended citation: Sanja Milivojevic, Mehdi Sobhani, Nicola Webb, Zachary Madin, James Ward, Sagir Yusuf, Chris Baber, and Edmund R Hunt. 2024. Swift Trust in Mobile Ad Hoc Human-Robot Teams. In Proceedings of the Second International Symposium on Trustworthy Autonomous Systems (TAS '24). Association for Computing Machinery, New York, NY, USA, Article 16, 1–10. https://doi.org/10.1145/3686038.3686057 Paper link here.
Published in ICDL - Austin, Texas, 2024
Individual differences in learning behavior within social groups have significant effects on collective task performance.
Recommended citation: Connor York, Zachary R. Madin, Paul O'Dowd, Edmund R. Hunt . (2024). "Shaping Multi-Robot Patrol Performance with Heterogeneity in Individual Learning Behavior." ICDL 2024. 1(1). Paper link here.
Published in ACM/SIGAPP - Avila, Spain, 2024
We find that generally, MRP algorithms that promote physical mixing of robots, as measured by a higher connectivity of their emergent communication network, reach consensus more quickly.
Recommended citation: Madin, Zachary R and Lawry, Jonathan and Hunt, Edmund R, . (2024). "Collective Anomaly Perception During Multi-Robot Patrol." SAC 2024 1. 1(1). Paper link here.
Published in Cranfield Defence and Security Doctoral Symposium, 2024
It is noted that algorithms that result in moderate levels of algebraic connectivity in the communication networks are robust to noise levels and result in high F-scores.
Published in MRS 2023 - Boston, USA, 2023
We find that generally, MRP algorithms that promote physical mixing of robots, as measured by a higher connectivity of their emergent communication network, reach consensus more quickly.