Uncertainty Estimation for Safe Human-Robot Collaboration using Conservation Measures

TL;DR

This paper introduces a real-time, data-driven method for quantifying measurement uncertainties in human-robot collaboration, using conservation measures to enhance safety and compliance with standards like ISO 13849.

Contribution

The novel approach leverages conservation equations to evaluate measurement uncertainties during operation, improving safety assessment in human-robot systems.

Findings

Validated on a human-robot collaboration use case

Uncertainty estimates can be mapped to safety standards

Enhances real-time safety monitoring in industrial environments

Abstract

We present an online and data-driven uncertainty quantification method to enable the development of safe human-robot collaboration applications. Safety and risk assessment of systems are strongly correlated with the accuracy of measurements: Distinctive parameters are often not directly accessible via known models and must therefore be measured. However, measurements generally suffer from uncertainties due to the limited performance of sensors, even unknown environmental disturbances, or humans. In this work, we quantify these measurement uncertainties by making use of conservation measures which are quantitative, system specific properties that are constant over time, space, or other state space dimensions. The key idea of our method lies in the immediate data evaluation of incoming data during run-time referring to conservation equations. In particular, we estimate violations of a-priori known, domain specific conservation properties and consider them as the consequence of measurement uncertainties. We validate our method on a use case in the context of human-robot collaboration, thereby highlighting the importance of our contribution for the successful development of safe robot systems under real-world conditions, e.g., in industrial environments. In addition, we show how obtained uncertainty values can be directly mapped on arbitrary safety limits (e.g, ISO 13849) which allows to monitor the compliance with safety standards during run-time.