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Affordance Templates (ATs) are a method for parameterizing objects forautonomous robot manipulations. In this approach, instances of an object areregistered by positioning a model in a 3D environment, which requires a largeamount of user input. We instead propose a registration method which combinesautonomy and user corrections. For selected objects, the system determines boththe model and corresponding pose autonomously. The user makes corrections onlyif the model or pose is incorrect. This method increases the level of autonomycompared to existing approaches which can reduce user input and time on task.In this paper, we present an overview of existing methods, a description of ourmethod, preliminary results, and planned future work.

Affordance Template Registration via Human-in-the-loop Corrections