Utilizing Dynamic Hazard Knowledge for Risk Sensitive Action Planning of Autonomous Robots

Autonomous robots are required to perform tasks
in complex and dynamic environments. For this class of systems,
traditional safety assuring methods are not satisfying due to
the unknown effects of the interacting system with an open
environment. Briefly speaking: What is not known during the
development phase can not be adequately considered. In order
to tackle this problem, it is proposed to extend the safety
measures with the so-called dynamic risk assessment. Therefore,
the anticipatory capability of a Cognitive Technical System, the
so-called mental action space, is utilized. The mental action space,
a learned internal representation for possible courses of action,
is dynamically assessed. The proposed dynamic risk assessment
module provides this functionality. The core are quantitative risk
models, so-called ‘safety principles’, which can be specified during
the system’s design stage without losing the possibility to be
adjusted or extended during the system’s operating time. Finally,
an exemplary application of the approach shows a robot, enabled
to safely plan and perform its tasks concerning risks arising due
to interaction of robot and environment.