An Ontology-based Hybrid Architecture for Planning and Robust Execution in Tabletop Scenarios

Alessio Capitanelli, Fulvio Mastrogiovanni
2016 International Conference of the Italian Association for Artificial Intelligence  
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 open
more » ... source, closed-loop hybrid architecture based on semantic knowledge and high-level reasoning to ground perception-based task representation, reasoning and execution. An ontology integrates perceptual cues with planning-relevant knowledge to automatically perform context assessment, infer when to act to modify the environment and to generate appropriate definitions of domains and problems to solve. An interface between the ontology and low-level motion planners allows for updating the representation at run-time, thus enforcing robustness versus unmodelled traits of the environment. The framework has been validated using a Baxter dual-arm manipulator operating in a tabletop scenario.
dblp:conf/aiia/CapitanelliM16 fatcat:swjqukybsbab7myxqsfrntiaeq