The Role of Cybersecurity and HPC in the Explainability of Autonomous Robots Behavior

Olivera, Vicente Matellán; Rodriguez-Lera, Francisco-J.; Guerrero-Higueras, Angel-M.; Rico, Francisco-Martin; Ginés, Jonatan

doi:10.1109/arso51874.2021.9542829

Cited by 2 publications

(2 citation statements)

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“…This formalization is illustrated in Figure 2. The presented diagram simplifies the process explained in Matellán et al (2021). There we can see a set of observable robot behaviour, events and logging facts.…”

Section: Formalizationmentioning

confidence: 99%

“…The accountability system should be faced from a middleware‐free approach, for this reason, this research has been working in a three layer approach described in previous research (Matellán et al, 2021; Rodríguez‐Lera et al, 2019; Rodríguez‐Lera, Santamarta, et al, 2020). However, the authors also believe that the accountability system should be faced from any of the most extended robotic middleware.…”

Section: Introductionmentioning

confidence: 99%

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Towards explainability in robotics: A performance analysis of a cloud accountability system

et al. 2022

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Understanding why a robot's behaviour was triggered is a growing concern to get human‐acceptable social robots. Every action, expected and unexpected, should be able to be explained and audited. The formal model proposed here deals with different information levels, from low‐level data, such as sensors' data logging; to high‐level data that provide an explanation of the robot's behaviour. This study examines the impact on the robot system of a custom log engine based on a custom ROS logging node and investigates pros and cons when used together with a NoSQL database locally and in a cloud environment. Results allow to characterize these alternatives and explore the best strategy for offering a fully log‐based accountability engine that maximizes the mapping between robot behaviour and robot logs.

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Section: Formalizationmentioning

confidence: 99%