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- W4312458032 abstract "Automatic control design for robotic systems is becoming more and more popular. However, this usually involves a significant computational cost, due to the expensive and noisy evaluation of candidate solutions through high-fidelity simulation or even real hardware. This work aims at reducing the computational cost of automatic design of behavioral arbitrators through the introduction of a two-step approach. In the first step, the structure of the finite state machine governing the behavioral arbitrator is optimized. To this purpose, a more abstracted model of the robotic system is leveraged in order to significantly reduce the computational cost. In the second step, the close-to-hardware, behavioral parameters are fine-tuned using a high-fidelity model. We show that, for a scenario involving a single robot and multiple tasks to be solved sequentially, using the proposed method results in a significant decrease of the computational cost while reaching the same controller performance both in simulation and reality." @default.
- W4312458032 created "2023-01-04" @default.
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- W4312458032 date "2022-10-23" @default.
- W4312458032 modified "2023-10-16" @default.
- W4312458032 title "Leveraging Multi-Level Modelling to Automatically Design Behavioral Arbitrators in Robotic Controllers" @default.
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- W4312458032 doi "https://doi.org/10.1109/iros47612.2022.9981817" @default.
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