arXiv subjects

Yusuke Goto

Publications and source records attributed to Yusuke Goto.

4 recordsLinked to original sources

arXiv2026

Shepherding UAV Swarm with Action Prediction Based on Movement Constraints

In this study, we propose a new sheepdog-inspired control method for a swarm of small unmanned aerial vehicles (UAVs), which predicts the swarm behavior while explicitly accounting for the motion constraints of real robots. Sheepdog-inspired guidance control refers to a framework in which a small number of navigator agents (sheepdog agents) indirectly drive a large number of autonomous agents (a flock of sheep agents) so as to steer the group toward a target position. In conventional studies on sheepdog-inspired guidance, both types of agents have typically been modeled as point masses, and the guidance law for the navigator agents has been designed using simple interaction vectors based on the instantaneous relative positions between the agents. However, when implementing such methods on real robots such as drones, it is necessary to consider each agent's motion constraints, including upper bounds on velocity and acceleration. Moreover, we argue that guidance can be made more efficient by predicting the future behavior of the autonomous swarm that is observable to the navigator agents. To this end, we propose a three-dimensional guidance control law based on behavior prediction of autonomous agents under motion constraints, inspired by the Dynamic Window Approach (DWA). At each control cycle, the navigator agent generates a set of feasible motion candidates that satisfy its motion constraints, and predicts the short-horizon swarm evolution using an internal model of the autonomous agents maintained within the navigator agent. The motion candidates are then evaluated according to criteria such as the progress velocity toward the target, the positioning strategy with respect to the swarm, and safety margins, and the optimal motion is selected to achieve safe and efficient guidance. Numerical simulation results demonstrate the effectiveness of the proposed guidance control law.

cs.RO↗

arXiv2021

Observing and modeling the sequential pairwise reactions that drive solid-state ceramic synthesis

Solid-state synthesis from powder precursors is the primary processing route to advanced multicomponent ceramic materials. Designing ceramic synthesis routes is usually a laborious, trial-and-error process, as heterogeneous mixtures of powder precursors often evolve through a complicated series of reaction intermediates. Here, we show that phase evolution from multiple precursors can be modeled as a sequence of pairwise interfacial reactions, with thermodynamic driving forces that can be efficiently calculated using ab initio methods. Using the synthesis of the classic high-temperature superconductor YBa$_2$Cu$_3$O$_{6+x}$ (YBCO) as a representative system, we rationalize how replacing the common BaCO$_3$ precursor with BaO$_2$ redirects phase evolution through a kinetically-facile pathway. Our model is validated from in situ X-ray diffraction and in situ microscopy observations, which show rapid YBCO formation from BaO$_2$ in only 30 minutes. By combining thermodynamic modeling with in situ characterization, we introduce a new computable framework to interpret and ultimately design synthesis pathways to complex ceramic materials.

cond-mat.mtrl-sci↗

arXiv2015

Purely hydrodynamic ordering of rotating disks at a finite Reynolds number

Self-organization of moving objects in hydrodynamic environments has recently attracted considerable attention in connection to natural phenomena and living systems. However, the underlying physical mechanism is much less clear due to the intrinsically nonequilibrium nature, compared with self-organization of thermal systems. Hydrodynamic interactions are believed to play a crucial role in such phenomena. To elucidate the fundamental physical nature of many-body hydrodynamic interactions at a finite Reynolds number, here we study a system of co-rotating hard disks in a two-dimensional viscous fluid at zero temperature. Despite the absence of thermal noise, this system exhibits rich phase behaviours, including a fluid state with diffusive dynamics, a cluster state, a hexatic state, a glassy state, a plastic crystal state and phase demixing.We reveal that these behaviours are induced by the off-axis and many-body nature of nonlinear hydrodynamic interactions and the finite time required for propagating the interactions by momentum diffusion.

cond-mat.soft↗

arXiv2013

Minimal Model for Stem-Cell Differentiation

To explain the differentiation of stem cells in terms of dynamical systems theory, models of interacting cells with intracellular protein expression dynamics are analyzed and simulated. Simulations were carried out for all possible protein expression networks consisting of two genes under cell--cell interactions mediated by the diffusion of a protein. Networks that show cell differentiation are extracted and two forms of symmetric differentiation based on Turing's mechanism and asymmetric differentiation are identified. In the latter network, the intracellular protein levels show oscillatory dynamics at a single-cell level, while cell-to-cell synchronicity of the oscillation is lost with an increase in the number of cells. Differentiation to a fixed-point type behavior follows with a further increase in the number of cells. The cell type with oscillatory dynamics corresponds to a stem cell that can both proliferate and differentiate, while the latter fixed-point type only proliferates. This differentiation is analyzed as a saddle-node bifurcation on an invariant circle, while the number ratio of each cell type is shown to be robust against perturbations due to self-consistent determination of the effective bifurcation parameter as a result of the cell--cell interaction. Complex cell differentiation is designed by combing these simple two-gene networks. The generality of the present differentiation mechanism, as well as its biological relevance, is discussed.

q-bio.CB↗