Using structural bootstrapping for object substitution in robotic executions of human-like manipulation tasks
In this work we address the problem of finding replacements of missing objects that are needed for the execution of human-like manipulation tasks. This is a usual problem that is easily solved by humans provided their natural knowledge to find object substitutions: using a knife as a screwdriver or a book as a cutting board. On the other hand, in robotic applications, objects required in the task should be included in advance in the problem definition. If any of these objects is missing from the scenario, the conventional approach is to manually redefine the problem according to the available objects in the scene. In this work we propose an automatic way of finding object substitutions for the execution of manipulation tasks. The approach uses a logic-based planner to generate a plan from a prototypical problem definition and searches for replacements in the scene when some of the objects involved in the plan are missing. This is done by means of a repository of objects and attributes with roles, which is used to identify the affordances of the unknown objects in the scene. Planning actions are grounded using a novel approach that encodes the semantic structure of manipulation actions. The system was evaluated in a KUKA arm platform for the task of preparing a salad with successful results.