Bayesian learning for the robust verification of autonomous robots
Abstract Autonomous robots used in infrastructure inspection, space exploration and other critical missions operate in highly dynamic environments. As such, they must continually verify their ability to complete the tasks associated with these missions safely and effectively. Here we present a Bayes...
| Main Authors: | Xingyu Zhao, Simos Gerasimou, Radu Calinescu, Calum Imrie, Valentin Robu, David Flynn |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-01-01
|
| Series: | Communications Engineering |
| Online Access: | https://doi.org/10.1038/s44172-024-00162-y |
Similar Items
-
Efficient synthesis of robust models for stochastic systems
by: Calinescu, R, et al.
Published: (2018) -
RODES: A robust-design synthesis tool for probabilistic systems
by: Calinescu, R, et al.
Published: (2017) -
Designing robust software systems through parametric markov chain synthesis
by: Kwiatkowska, M, et al.
Published: (2017) -
Reliability and Safety of Autonomous Systems Based on Semantic Modelling for Self-Certification
by: Osama Zaki, et al.
Published: (2021-01-01) -
Symbiotic System of Systems Design for Safe and Resilient Autonomous Robotics in Offshore Wind Farms
by: Daniel Mitchell, et al.
Published: (2021-01-01)