Perception is a critical component of high-integrity applications of robotics and autonomous
systems, such as self-driving vehicles. In these applications, failure of perception systems …

This paper investigates runtime monitoring of perception systems. Perception is a critical
component of high-integrity applications of robotics and autonomous systems, such as self …

Sensing and Perception (S&P) is a crucial component of an autonomous system (such as a
robot), especially when deployed in highly dynamic environments where it is required to …

The reliability of autonomous driving sensing systems impacts the overall safety of the
driving system. However, perception system fault diagnosis is currently a weak area of …

Building datasets for autonomous vehicles has become an essential element of robotics
research. Numerous datasets were published, pushing the state-of-the-art forward. This …

Trustworthy environment perception is the fundamental basis for the safe deployment of
automated agents such as self-driving vehicles or intelligent robots. The problem remains …

The objective of this work is to provide a comprehensive understanding of the development
of autonomous vehicle perception systems. So far, most autonomy perception research has …

The application of machine learning (ML) based perception algorithms in safety-critical
systems such as autonomous vehicles have raised major safety concerns due to the …

Testing black-box perceptual-control systems in simulation faces two difficulties. Firstly,
perceptual inputs in simulation lack the fidelity of real-world sensor inputs. Secondly, for a …

Autonomous vehicles use cyber-physical systems to provide comfort and safety to
passengers. Design of safety mechanisms for such systems is hindered by the growing …