Statistical Model Checking of Human-Robot Interaction Scenarios

TL;DR

This paper demonstrates how statistical model checking using hybrid automata and Uppaal can verify properties of human-robot interaction scenarios, providing insights into system reliability and human factors.

Contribution

It introduces a framework for modeling human-robot interactions with hybrid automata and applies statistical model checking to analyze system properties and dynamics.

Findings

Probabilistic verification of properties in human-robot scenarios

Insights into time dynamics and human-related variables

Enhanced decision-making for system improvement

Abstract

Robots are soon going to be deployed in non-industrial environments. Before society can take such a step, it is necessary to endow complex robotic systems with mechanisms that make them reliable enough to operate in situations where the human factor is predominant. This calls for the development of robotic frameworks that can soundly guarantee that a collection of properties are verified at all times during operation. While developing a mission plan, robots should take into account factors such as human physiology. In this paper, we present an example of how a robotic application that involves human interaction can be modeled through hybrid automata, and analyzed by using statistical model-checking. We exploit statistical techniques to determine the probability with which some properties are verified, thus easing the state-space explosion problem. The analysis is performed using the Uppaal tool. In addition, we used Uppaal to run simulations that allowed us to show non-trivial time dynamics that describe the behavior of the real system, including human-related variables. Overall, this process allows developers to gain useful insights into their application and to make decisions about how to improve it to balance efficiency and user satisfaction.