Data-driven control of planar snake robot locomotion
| Autor: | M. L. Scarpa, B. Nortmann, K. Y. Pettersen, T. Mylvaganam |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Zdroj: | 61st IEEE Conference on Decision and Control 2022 IEEE 61st Conference on Decision and Control (CDC) |
| Popis: | A direct data-driven strategy for snake-robot lo- comotion control is proposed in this paper. The approach leads to a time-varying state feedback controller with robustness guarantees. Instead of relying on exact model knowledge - which is often not available in practice - the proposed control strategy requires only input-state data collected during offline experiments. The efficacy of the proposed strategy is demon- strated via simulations. Notably, by using data to compensate for inaccurate models, the proposed control strategy can lead to significant improvements in closed-loop performance com- pared to existing (model-based) control strategies, while also eliminating the need for manual tuning of control parameters. |
| Databáze: | OpenAIRE |
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