6 papers
Efficient Transfer Learning of Robot Dynamic Models Using Morphological Similarity
Pavlo Kupyn, Yuya Hamamatsu, Roza Gkliva +2
This study proposes a neural network-based transfer learning framework for modeling the dynamics of soft, fin-actuated underwater robots. We focus on morphologically similar robots…
Strouhal-Aware Model Predictive Control for Efficient Multi-Fin Flapping Locomotion
Yuya Hamamatsu, Zixi Chen, Maarja Kruusmaa +1
Efficient flapping propulsion hinges on operating within a narrow Strouhal number window, a principle nature has converged upon for maximum thrust-to-power ratio. We translate this…
Layout-independent actuation allocator for fin-actuated marine robots
Yuya Hamamatsu, Maarja Kruusmaa, Asko Ristolainen
In this study, we propose a layout-independent control allocator capable of zero-shot deployment across diverse actuator configurations. The proposed method utilizes a learning pip…
Efficient Control Allocation and 3D Trajectory Tracking of a Highly Manoeuvrable Under-actuated Bio-inspired AUV
Walid Remmas, Christian Meurer, Yuya Hamamatsu +2
Fin actuators can be used for for both thrust generation and vectoring. Therefore, fin-driven autonomous underwater vehicles (AUVs) can achieve high maneuverability with a smaller…
Cross-platform Learning-based Fault Tolerant Surfacing Controller for Underwater Robots
Yuya Hamamatsu, Walid Remmas, Jaan Rebane +2
In this paper, we propose a novel cross-platform fault-tolerant surfacing controller for underwater robots, based on reinforcement learning (RL). Unlike conventional approaches, wh…
Underwater Soft Fin Flapping Motion with Deep Neural Network Based Surrogate Model
Yuya Hamamatsu, Pavlo Kupyn, Roza Gkliva +2
This study presents a novel framework for precise force control of fin-actuated underwater robots by integrating a deep neural network (DNN)-based surrogate model with reinforcemen…