Robot design support system based on interactive evolutionary computation using Boltzmann selection

Recently, the need of users is changing to the efficient quality of functions with the sophisticated design and reasonable price. Furthermore, current users prefer to the personal customization of products. Accordingly, a design support system is useful and helpful for non-expert people to design products easily, but such non-expert people might take much time and load in the product design. Therefore, we proposed interactive design support system based on evolutionary computation, and applied the proposed method to the design of robot partners. However, it is very difficult to reflect human evaluation to the generation of the next design candidates. Therefore, we propose an estimation method of human evaluation using fuzzy inference in the interactive design support using the evolutionary computation. Furthermore, we use iPhone simulator to evaluate the human impression based on direct interaction with the designed robot partner. Finally, we discuss the effectiveness of the proposed system through several simulation and experimental results.

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