Knowledge Driven Robotics (KDR)

This paper presents a software architecture that enables practical deployment of robotic systems in roles that require the execution of tasks not well-defined at design time. The paradigm employed is a maximization of reuse, generalization, and interoperability of logical structures and robot tasks which can readily be composited, supporting a robust and flexible autonomy stack. The Knowledge Driven Robotics (KDR) software architecture achieves this by offering a unique set of interactions between symbolic planning, Behavior Trees, and database information. New composite tasks can readily be composed of highly parameterized atomic tasks to manipulate known classes of task objects. Key contributions include the ability of the behavior layer to query, transform, and utilize data in a flexible manner and to act as data management systems during execution, as well as surrounding infrastructure enabling the treatment of data as a first-class citizen.