  Although autonomous functioning facilitates deployment of robotic systems in
domains that admit limited human oversight on our planet and beyond, finding
correspondence between task requirements and autonomous capability is still an
open challenge. Consequently, a number of methods for quantifying autonomy have
been proposed over the last three decades, but to our knowledge all these have
no discernment of sub-mode features of variation of autonomy and some are based
on metrics that violet the Goodhart's law. This paper focuses on the full
autonomous mode and proposes a quantitative autonomy assessment framework based
on task requirements. The framework starts by establishing robot task
characteristics from which three autonomy metrics, namely requisite capability
set, reliability and responsiveness are derived. These characteristics were
founded on the realization that robots ultimately replace human skilled
workers, from which a relationship between human job and robot task
characteristics was established. Additionally, mathematical functions mapping
metrics to autonomy as a two-part measure, namely of level and degree of
autonomy are also presented. The distinction between level and degree of
autonomy stemmed from the acknowledgment that autonomy is not just a question
of existence, but also one of performance of requisite capability. The
framework has been demonstrated on two case studies, namely autonomous vehicle
at an on-road dynamic driving task and the DARPA subterranean challenge rules
analysis. The framework provides not only a tool for quantifying autonomy, but
also a regulatory interface and common language for autonomous systems
developers and users. Its greatest feature is the ability to monitor system
integrity when implemented online.
