Execution of a dual-object (pushing) action with semantic event chains

Presentado en 11th IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS), Bled, Slovenia, 26-28 October, 2011.Execution of a manipulation after learning from demonstration many times requires intricate planning and control systems or some form of manual guidance for a robot. Here we present a framework for manipulation execution based on the so called “Semantic Event Chain” which is an abstract description of relations between the objects in the scene. It captures the change of those relations during a manipulation and thereby provides the decisive temporal anchor points by which a manipulation is critically defined. Using semantic event chains a model of a manipulation can be learned. We will show that it is possible to add the required control parameters (the spatial anchor points) to this model, which can then be executed by a robot in a fully autonomous way. The process of learning and execution of semantic event chains is explained using a box pushing example.The research leading to these results has received funding from the European Community’s Seventh Framework Programme FP7/2007-2013 (Specific Programme Cooperation, Theme 3, Information and Communication Technologies) under grant agreement no. 270273, Xperience and grant agreement no. 269959, IntellAct. B.D. acknowledges support from the Spanish Ministry for Science and Innovation via a Ramon y Cajal Fellowship.Peer reviewe

Execution of a dual-object (pushing) action with semantic event chains

Execution of a manipulation after learning from demonstration many times requires intricate planning and control systems or some form of manual guidance for a robot. Here we present a framework for manipulation execution based on the so called “Semantic Event Chain” which is an abstract description of relations between the objects in the scene. It captures the change of those relations during a manipulation and thereby provides the decisive temporal anchor points by which a manipulation is critically defined. Using semantic event chains a model of a manipulation can be learned. We will show that it is possible to add the required control parameters (the spatial anchor points) to this model, which can then be executed by a robot in a fully autonomous way. The process of learning and execution of semantic event chains is explained using a box pushing example

Execution of a dual-object (pushing) action with semantic event chains

Execution of a manipulation after learning from demonstration many times requires intricate planning and control systems or some form of manual guidance for a robot. Here we present a framework for manipulation execution based on the so called “Semantic Event Chain” which is an abstract description of relations between the objects in the scene. It captures the change of those relations during a manipulation and thereby provides the decisive temporal anchor points by which a manipulation is critically defined. Using semantic event chains a model of a manipulation can be learned. We will show that it is possible to add the required control parameters (the spatial anchor points) to this model, which can then be executed by a robot in a fully autonomous way. The process of learning and execution of semantic event chains is explained using a box pushing exampleVytauto Didžiojo universiteta