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The aim of this work is to develop a task representation and execution framework for dual-arm manipulators operating in tabletop scenarios. In particular, we want to enforce robot's autonomy, robustness to failures, and (in perspective) a natural human-robot interaction. To this purpose, the framework integrates (i) point cloud perception, (ii) ontology-based knowledge representation, (iii) high-level task planning, as well as (iv) task execution and monitoring. Our main contribution is an opendblp:conf/aiia/CapitanelliM16 fatcat:swjqukybsbab7myxqsfrntiaeq