A neural network model together with feature-based model translates the input pattern into a design. Based on the design, assembly plans are generated for practical use in a single-robot assembly workcell. A feasible assembly plan that minimizes tool changes and subassembly reorientations is generated from the system. The automated assembly planning system presented here draws input relationships directly from the conceptual design and the geometry of the assembly. The system developed under this study extracts all reasoning information from the product model and permits the components to be assembled in a multitude of directions.
Several experiments illustrate the effectiveness of the designed assembly planning system.
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