  There is a growing demand for mobile robots to operate in more variable
environments, where guaranteeing safe robot navigation is a priority, in
addition to time performance. To achieve this, current solutions for local
planning use a specific configuration tuned to the characteristics of the
application environment. In this paper, we present an approach for developing
quality models that can be used by a self-adaptation framework to adapt the
local planner configuration at run-time based on the perceived environment. We
contribute a definition of a safety model that predicts the safety of a
navigation configuration given the perceived environment. Experiments have been
performed in a realistic navigation scenario for a retail application to
validate the obtained models and demonstrate their integration in a
self-adaptation framework.
