Bridging the gap between Discrete Symbolic Planning and Optimization-based Robot Control

Symbolic reasoners generate plans which are often not exploiting the robot capabilities and are sensitive to runtime disturbances. This work proposes a scheduler as an interface between a discrete, symbolic plan and a motion control based on constraint optimization. Acting as a local reasoner, the scheduler valuates a set of predicates to decide if an action should be executed or not. Given a task specification which describes how the action should be realized, the scheduler configures the controller at runtime. A demonstration will be provided considering an open drawer scenario.status: publishe