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

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.

Automated summary

Developing robotic applications with human-robot interaction for the service sector is challenging. The behavior of humans, who can deviate from the plan in various ways, creates uncertainty for the mission. We present a model-driven framework for developing interactive service robotic scenarios, which allows designers to model, estimate, deploy, and reconfigure the application.