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Kotaro Yasui

Publications and source records attributed to Kotaro Yasui.

3 recordsLinked to original sources

Dense-Joint-Based Obstacle-Aided Locomotion with a Joint-Repositionable Snake Robot

Obstacle-aided locomotion is a fundamental capability for snake robots to traverse complex environments. However, conventional rigid-link snake robots often suffer from stagnation or jamming caused by their low joint density (i.e., the number of joints per unit length). This results in discontinuous contact with obstacles, unlike the continuous adaptation of biological snakes. To investigate the effect of joint density on obstacle-aided locomotion performance, we utilized a joint-repositionable snake robot mechanism that decouples actuators from joints, enabling a high-density architecture. We developed two experimental models with identical total lengths but different joint densities (high-density and low-density) and conducted comparative propulsion experiments in obstacle environments with varying obstacle diameters. The experimental results demonstrate that the high-density model substantially suppresses the abrupt shifts in reaction forces that cause stagnation in the low-density model. By maintaining smooth contact points, the high-density configuration reduces power consumption and achieves stable, continuous propulsion. These results highlight high joint density as a key factor in improving the environmental adaptability of snake robots in complex terrains.

cs.RO↗

Behaviour diversity in a walking and climbing centipede-like virtual creature

Robot controllers are often optimised for a single robot in a single environment. This approach proves brittle, as such a controller will often fail to produce sensible behavior for a new morphology or environment. In comparison, animal gaits are robust and versatile. By observing animals, and attempting to extract general principles of locomotion from their movement, we aim to design a single decentralised controller applicable to diverse morphologies and environments. The controller implements the three components 1) undulation, 2) peristalsis, and 3) leg motion, which we believe are the essential elements in most animal gaits. The controller is tested on a variety of simulated centipede-like robots. The centipede is chosen as inspiration because it moves using both body contractions and legged locomotion. For a controller to work in qualitatively different settings, it must also be able to exhibit qualitatively different behaviors. We find that six different modes of locomotion emerge from our controller in response to environmental and morphological changes. We also find that different parts of the centipede model can exhibit different modes of locomotion, simultaneously, based on local morphological features. This controller can potentially aid in the design or evolution of robots, by quickly testing the potential of a morphology, or be used to get insights about underlying locomotion principles in the centipede.

cs.RO↗

An agent-based model for interrelation between COVID-19 outbreak and economic activities

As of July, 2020, acute respiratory syndrome caused by coronavirus COVID-19 is spreading over the world and causing severe economic damages. While minimizing human contact is effective in managing the outbreak, it causes severe economic losses. Strategies solving this dilemma by considering interrelation between the spread of the virus and economic activities are in urgent needs for mitigating the health and economic damage. Here we propose an abstract agent-based model for the outbreak of COVID-19 in which economic activities are taken into account. The computational simulation of the model recapitulated the trade-off between health and economic damage associated with lockdown measures. Based on the simulation results, we discuss how macroscopic dynamics of infection and economy emerge from the individuals' behaviours. We believe our model can serve as a platform for discussing solutions to the abovementioned dilemma.

physics.soc-ph↗