In this paper, we propose a modularized architecture for a robot arm object fetching system integrated with 3D CAD-model based object recognition system that can cope with objects in random types and poses. The interface and the core functionality of each module in the architecture are discussed in detail. Implementation of each module is also conducted. Furthermore, the assumptions and the working conditions behind each module are carefully examined. We develop the system based on our previous work and enhance the recognition module. To proof the feasibility of our architecture, 3D object recognition and fetching demonstration are successfully implemented, and the result of object recognition, teaching by touching, and fast grasp synthesis are successfully demonstrated.
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