Constraint-based Action Specification for bridging the gap between Symbolic and Control-theoretic Action Execution

In this paper we propose a bridge between a symbolic reasoning system and a task function based controller. We suggest to use modular positionand force constraints, which are represented as action-object-object triples on the symbolic side and as task function parameters on the controller side. This description is a considerably more fine-grained interface than what has been seen in high-level planners before. It can preserve the ’null space’ of the task and make it available to the control level. We demonstrate how a symbolic description can be translated to a control-level description that is executable on the robot. We describe the relation to existing robot knowledge bases and indicate information sources for generating constraints on the symbolic side. On the control side we then show how our approach outperforms a traditional controller, by exploiting the tasks null space, leading to a significantly extended work space.