  This paper outlines a roadmap to effectively leverage shared mental models in
multi-robot, multi-stakeholder scenarios, drawing on experiences from the
BugWright2 project. The discussion centers on an autonomous multi-robot systems
designed for ship inspection and maintenance. A significant challenge in the
development and implementation of this system is the calibration of trust. To
address this, the paper proposes that trust calibration can be managed and
optimized through the creation and continual updating of shared and accurate
mental models of the robots. Strategies to promote these mental models,
including cross-training, briefings, debriefings, and task-specific elaboration
and visualization, are examined. Additionally, the crucial role of an
adaptable, distributed, and well-structured user interface (UI) is discussed.
