arXiv subjects

Ko Yamamoto

Publications and source records attributed to Ko Yamamoto.

8 recordsLinked to original sources

arXiv2026

Dynamics Computation of Soft-Rigid Hybrid-Link System and Its Application to Motion Analysis of an Athlete Wearing Sport Prosthesis

This paper presents a motion analysis framework for an athlete wearing sport-specific flexible prosthesis based on the soft-rigid hybrid-link system. Such a motion analysis is a challenging problem because we need to consider the interaction force between the rigid human skeleton system and a flexible prosthesis. However, most of human musculoskeletal models are based on the computation framework of a rigid-body multi-link system. Recently in soft robotics research field, fast and efficient modeling methods were developed for a flexible rod deformation, which allows us to build a hybrid-link system that integrates rigid-link and soft-bodies in a unified formulation. We apply inverse kinematics of the hybrid-link system to motion reconstruction from a motion captured data, and also present the estimation of the joint torques and ground reaction force by inverse dynamics. Through a human subject experiment, we show that the inverse dynamics achieved approximately 12% error on the ground reaction force estimation. Furthermore, we provide the muscle force estimation considering muscle amputation and interaction force with the prosthesis leg deformation.

cs.RO↗

arXiv2026

Simulation of Adaptive Running with Flexible Sports Prosthesis using Reinforcement Learning of Hybrid-link System

This study proposes a reinforcement learning-based framework for adaptive running motion simulation in a unilateral transtibial amputee using a hybrid-link system that incorporates the flexibility of a leaf-spring-type sports prosthesis. The design and selection of sports prostheses typically rely on trial and error. A comprehensive whole-body dynamics analysis that accounts for interactions between human motion and prosthetic deformation can provide valuable insights for user-specific design and selection. The proposed hybrid-link system enables such analysis by integrating a Piece-wise Constant Strain (PCS) model to represent prosthetic flexibility. Based on this system, the simulation methodology generates whole-body dynamic motions of a unilateral transtibial amputee using a reinforcement learning approach. This framework integrates imitation learning based on motion capture data with accurate computation of prosthetic dynamics. Running motions are simulated under multiple virtual prosthetic stiffness conditions, and the corresponding metabolic cost of transport (COT) obtained from these simulations is analyzed. The results suggest that variations in prosthetic stiffness influence running dynamics and performance, and that COT is consistent with values reported in prior study. Our findings demonstrate the potential of the proposed approach for simulation and analysis under virtual conditions that differ from real-world conditions.

cs.RO↗

arXiv2026

Design Methodology of Hydraulically-driven Soft Robotic Gripper for a Large and Heavy Object

This paper presents a design methodology of a hydraulically-driven soft robotic gripper for grasping a large and heavy object -- approximately 10 - 20 kg with 20 - 30 cm diameter. Most existing soft grippers are pneumatically actuated with several hundred kPa pressure, and cannot generate output force sufficient for such a large and heavy object. Instead of pneumatic actuation, hydraulic actuation has a potential to generate much larger power by several MPa pressure. In this study, we develop a hydraulically-driven soft gripper, in which its basic design parameters are determined based on a mathematical model that represents the relationship among the driving pressure, bending angle, object mass and grasping force. Moreover, we selected materials suitable for grasping a heavier object, based on the finite element analysis result of the detailed design. We report experimental results on a 20 kg object grasping and closed-loop control of the finger bending angle.

cs.RO↗

arXiv2025

ShibuyaSocial: Multi-scale Model of Pedestrian Flows in Scramble Crossing

This paper presents a learning-based model of pedestrian flows that integrates multi scale behaviors such as global route selection and local collision avoidance in urban spaces, particularly focusing on pedestrian movements at Shibuya scramble crossing. Since too much congestion of pedestrian flows can cause serious accidents, mathematically modeling and predicting pedestrian behaviors is important for preventing such accidents and providing a safe and comfortable environment. Although numerous studies have investigated learning-based modeling methods, most of them focus only on the local behavior of pedestrians, such as collision avoidance with neighbors and environmental objects. In an actual environment, pedestrian behavior involves more complicated decision making including global route selection. Moreover, a state transition from stopping to walking at a traffic light should be considered simultaneously. In this study, the proposed model integrates local behaviors with global route selection, using an Attention mechanism to ensure consistent global and local behavior predictions. We recorded video data of pedestrians at Shibuya scramble crossing and trained the proposed model using pedestrian walking trajectory data obtained from the video. Simulations of pedestrian behaviors based on the trained model qualitatively and quantitatively validated that the proposed model can appropriately predict pedestrian behaviors.

cs.MA↗

arXiv2025

Adaptive-twist Soft Finger Mechanism for Grasping by Wrapping

This paper presents a soft robot finger capable of adaptive-twist deformation to grasp objects by wrapping them. For a soft hand to grasp and pick-up one object from densely contained multiple objects, a soft finger requires the adaptive-twist deformation function in both in-plane and out-of-plane directions. The function allows the finger to be inserted deeply into a limited gap among objects. Once inserted, the soft finger requires appropriate control of grasping force normal to contact surface, thereby maintaining the twisted deformation. In this paper, we refer to this type of grasping as grasping by wrapping. To achieve these two functions by a single actuation source, we propose a variable stiffness mechanism that can adaptively change the stiffness as the pressure is higher. We conduct a finite element analysis (FEA) on the proposed mechanism and determine its design parameter based on the FEA result. Using the developed soft finger, we report basic experimental results and demonstrations on grasping various objects.

cs.RO↗

arXiv2025

Effect of Haptic Feedback on Avoidance Behavior and Visual Exploration in Dynamic VR Pedestrian Environment

Human crowd simulation in virtual reality (VR) is a powerful tool with potential applications including emergency evacuation training and assessment of building layout. While haptic feedback in VR enhances immersive experience, its effect on walking behavior in dense and dynamic pedestrian flows is unknown. Through a user study, we investigated how haptic feedback changes user walking motion in crowded pedestrian flows in VR. The results indicate that haptic feedback changed users' collision avoidance movements, as measured by increased walking trajectory length and change in pelvis angle. The displacements of users' lateral position and pelvis angle were also increased in the instantaneous response to a collision with a non-player character (NPC), even when the NPC was inside the field of view. Haptic feedback also enhanced users' awareness and visual exploration when an NPC approached from the side and back. Furthermore, variation in walking speed was increased by the haptic feedback. These results suggested that the haptic feedback enhanced users' sensitivity to a collision in VR environment.

cs.HC↗

arXiv2024

Viscoelasticity Estimation of Sports Prosthesis by Energy-minimizing Inverse Kinematics and Its Validation by Forward Dynamics

In this study, we present a method for estimating the viscoelasticity of a leaf-spring sports prosthesis using advanced energy minimizing inverse kinematics based on the Piece-wise Constant Strain (PCS) model to reconstruct the three-dimensional dynamic behavior. Dynamic motion analysis of the athlete and prosthesis is important to clarify the effect of prosthesis characteristics on foot function. However, three-dimensional deformation calculations of the prosthesis and viscoelasticity have rarely been investigated. In this letter, we apply the PCS model to a prosthesis deformation, which can calculate flexible deformation with low computational cost and handle kinematics and dynamics. In addition, we propose an inverse kinematics calculation method that is consistent with the material properties of the prosthesis by considering the minimization of elastic energy. Furthermore, we propose a method to estimate the viscoelasticity by solving a quadratic programming based on the measured motion capture data. The calculated strains are more reasonable than the results obtained by conventional inverse kinematics calculation. From the result of the viscoelasticity estimation, we simulate the prosthetic motion by forward dynamics calculation and confirm that this result corresponds to the measured motion. These results indicate that our approach adequately models the dynamic phenomena, including the viscoelasticity of the prosthesis.

cs.RO↗

arXiv2023

Asymptotic solution to a fuzzy elementary cellular automaton of rule number 38

Fuzzy cellular automaton is a dynamical system with a continuous state value embedding a cellular automaton with a discrete state value. We investigate a fuzzy cellular automaton obtained from an elementary cellular automaton of rule number 38. Its asymptotic solutions are classified into two types. One is a solution where stable propagating waves exist, and the other is a static uniform solution of constant value.

nlin.CG↗