A formal method for assessing the impact of task-based erroneous human behavior on system safety

Bolton, Matthew L.; Molinaro, Kylie A.; Houser, Adam

doi:10.1016/j.ress.2019.03.010

Cited by 16 publications

(1 citation statement)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By definition, these models reflect the expected behaviour of the human, which leads to correct execution of the task, and do not focus on reflecting erroneous behaviour [11]. Recently, however, Bolton et al [13] put together a task-based taxonomy of erroneous human behaviour that allows errors to be modelled as divergences from task models; Li et al [47] uses an analytic hierarchy process to identify hazards and increase the efficiency of the executing task.…”

Section: Task-analytic Modelsmentioning

confidence: 99%

How to Formally Model Human in Collaborative Robotics

Askarpour

2020

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

Human-robot collaboration (HRC) is an emerging trend of robotics that promotes the co-presence and cooperation of humans and robots in common workspaces. Physical vicinity and interaction between humans and robots, combined with the uncertainty of human behaviour, could lead to undesired situations where humans are injured. Thus, safety is a priority for HRC applications. Safety analysis via formal modelling and verification techniques could considerably avoid dangerous consequences, but only if the models of HRC systems are comprehensive and realistic, which requires reasonably realistic models of human behaviour. This paper explores state-of-the-art solutions for modelling human and discusses which ones are suitable for HRC scenarios.

show abstract

Section: Task-analytic Modelsmentioning

confidence: 99%

How to Formally Model Human in Collaborative Robotics

Askarpour

2020

Electron. Proc. Theor. Comput. Sci.

View full text Add to dashboard Cite

show abstract

Analyzing the impact of human errors on interactive service robotic scenarios via formal verification

Lestingi,

Manglaviti,

Marinaro

et al. 2023

Softw Syst Model

View full text Add to dashboard Cite

Developing robotic applications with human–robot interaction for the service sector raises a plethora of challenges. In these settings, human behavior is essentially unconstrained as they can stray from the plan in numerous ways, constituting a critical source of uncertainty for the outcome of the robotic mission. Application designers require accessible and reliable frameworks to address this issue at an early development stage. We present a model-driven framework for developing interactive service robotic scenarios, allowing designers to model the interactive scenario, estimate its outcome, deploy the application, and smoothly reconfigure it. This article extends the framework compared to previous works by introducing an analysis of the impact of human errors on the mission’s outcome. The core of the framework is a formal model of the agents at play—the humans and the robots—and the robotic mission under analysis, which is subject to statistical model checking to estimate the mission’s outcome. The formal model incorporates a formalization of different human erroneous behaviors’ phenotypes, whose likelihood can be tuned while configuring the scenario. Through scenarios inspired by the healthcare setting, the evaluation highlights how different configurations of erroneous behavior impact the verification results and guide the designer toward the mission design that best suits their needs.

show abstract