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The authors have been developing a novel method for programming a robot, called the assembly-plan-from-observation (APO) method. The APO method aims to build a system that has threefold capabilities. It observes a human performing an assembly task, it understands the task based on this observation, and it generates a robot program to achieve the same task. This paper concentrates on the APO's main loop, which is task recognition. Using object recognition results, the task recognition module determines what kind of assembly task is performed. A previous system, recognizes assembly tasks which only handle polyhedral objects. The system reported here handles curved objects and other mechanical contacts as well. The authors define task models for these cases and show that task models are useful in recognizing assembly tasks, and that it is possible to generate robot motion commands for repeating the same assembly task.
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Ikeuchi et al. (2002) studied this question.
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