ABSTRACT This paper presents a prototype XR system for disaster medical response, demonstrating the feasibility of real‐time interactive elastodynamics simulations in emergency scenarios. The system delivers an end‐to‐end workflow utilizing XR technology, from on‐site data acquisition to remote simulation. Specifically, we propose an image‐guided mesh‐processing pipeline that converts photographs of injured individuals into solver‐ready tetrahedral meshes. We also develop a constraint‐based elastodynamics solver capable of simulating deformable bodies and visualizing internal stresses. Additionally, the system integrates multiple advanced XR devices and addresses the coordinate‐alignment problem between these devices and the simulator. We validate the system's performance in both AR/VR modes, under textured and stress‐visualization configurations, and demonstrate its applicability for remote medical guidance. Beyond whole‐body elastic simulations, we conduct preliminary organ‐level experiments to inform future remote surgical applications. This prototype, validated using a two‐room setup, provides a feasible solution for remote emergency medical response.

Position Based Dynamics (PBD) has been widely adopted for interactive simulation, particularly in applications such as virtual surgery and elastodynamics. However, many existing frameworks focus exclusively on interactive deformation, often neglecting the comprehensive analysis of stress distribution, which is a critical factor in engineering assessments. In remote disaster rescue scenarios, real-time stress visualization can provide vital insights that enable rescue teams to make informed decisions when interacting with deformable objects. In this work, we introduce a fully GPU-parallel, stress-driven simulation framework for real-time deformable human body dynamics, specifically designed for disaster rescue applications. Our approach computes the von Mises stress for each tetrahedral element using a practical Neo-Hookean material model, projects the stress onto the corresponding mesh vertices, and maps these values onto the surface for intuitive rendering. In particular, we address the convergence limitations of general Neo-Hookean constraints under a Jacobi parallel scheme by developing a robust, improved approach. This improved approach avoids the typical volume loss observed in conventional methods and better replicates the qualitative behavior of the Gauss-Seidel scheme. Quantitative experiments using 100 human body models with diverse shapes, heights, and weights demonstrate that our framework effectively maintains the original pose while delivering enhanced physical realism and informative stress visualization. This capability provides disaster rescue teams with critical insights to optimize decision-making during emergencies.

This paper proposes a method of presenting intuitively easy-to-grasp images by merging the images of an around view monitor and a back-view monitor into a single image. In the proposed method, the viewpoint automatically changes as the vehicle moves, enabling the display of an overhead 3D image that always shows the vehicle. This video generation is composed of simple image deformation by projective transformation, which serves as a distortion correction as well as a viewpoint change. Experiments conducted in a parking situation showed that the system automatically switches the 3D viewpoint depending on the distance to the parking position to present an easy-to-understand image including the surrounding environment.

In this study, force sensorless plastic deformation control is designed and implemented. This control strategy is derived based on the concept that the shift in position and posture attributable to an external force as the deformation of the robot. The Maxwell model that describes plastic deformation is derived as the simple compressed expression using the convolution. Based on the expression, a control law that does not require force information is proposed by not performing the inertia shaping. Physical simulation with a robotic arm are executed to validate the proposed control law.

We propose an accurate and robust inter-vehicle distance estimation method using highspeed stereo vision. The framework involves two phases: a tracking phase, wherein a preceding vehicle is accurately and stably tracked by a tracking algorithm optimized for stereo high-speed vision, and a distance estimation phase, wherein the inter-vehicle distance is estimated via a highly accurate scale estimation and aggregation method for multiple scale-based distance estimations to ensure that it is more accurate and robust without introducing a delay. Further, we propose patch multiplexing to realize accurate and efficient aggregation even in situations where the scale changes rapidly (e.g., emergency braking). Through comparative analysis using three real-world scenarios, we verify that the accuracy of inter-vehicle distance estimation using our approach is comparable to that of laser rangefinders. We also demonstrate that differential quantities, such as velocity and acceleration, could be accurately estimated using an adaptive Kalman filter. Our results will help develop safe and accurate truck platooning and adaptive cruise control systems.

In this study, a visual shock absorber capable of adapting to free-fall objects with various weights and speeds is designed and realized. The key element is a magnetic gear to passively absorb shock in the moment of contact, which is difficult for traditional feedback control to deal with. The magnetic gear allows the seamless transfer of control from the non-contact state to the contact state. 1000 Hz high-speed visual object tracking is used for preparation with position and velocity control in the object non-contact state. In the moment of object contact, the high backdrivability of the magnetic gear response by hardware provides high responsiveness to external force. After the impact, the plastic deformation control of a parallel-expressed Maxwell model handles the contact state.

In this study, Magripper, a highly backdrivable gripper, is developed to achieve high-speed hitting grasping executed seamlessly from reaching. The gripper is designed to achieve both high speed and environmental adaptability. The key element is backdrivability in terms of both hardware and control. In Magripper, a magnetic gear is introduced to passively absorb shock in the moment of contact as a means of hardware backdrivability, and backdrive control is implemented based on the Zener model. After developing a hitting grasping framework, high-speed hitting grasping tasks with a wood block, a wood cylinder, and a plastic coin are conducted using only servo control without sensors, such as cameras and tactile sensors. In particular, coin grasping with high-speed movement is very difficult because collisions with environmental objects such as the floor and desk, are likely, which may break a robot.

We developed a dual-camera-based multi-face zoom-tracking system that captures zoomed targets simultaneously by combining a mirror-drive pan-tilt camera with ultrafast gaze control for zoomed views and an RGB-D camera for 3D wide view. In our system, the RGB-D camera detects multiple persons in the wide view and outputs the 3-D positions of their keypoints with CNN-based pose estimation. The mirror-drive pan-tilt camera simultaneously switches its viewpoints to the directions of the nose keypoints to zoom on their face images to perform person identification. We demonstrate our system performance using experimental results of a 3-D people-flow analysis with person identification, where the mirror-drive pantilt camera with 120-viewpoints/s-switching functions effectively as five virtual 24-fps pan-tilt cameras to track and zoom on the faces of five walking persons in an indoor scene.

This study proposes a dynamic observable contact (DOC) hand as a new multifingered hand to ensure high- speed insertion in an assembly process with a small clearance between objects. To achieve insertion with a small clearance at high speed, a robot hand must realize both impact reduction and position-error compensation when the two objects contact each other. The DOC hand, with its features of 6-degrees-of- freedom dynamic passivity and object-pose observability, can realize both impact reduction and position-error compensation. To evaluate the effectiveness of the DOC hand, we construct a robot system using the DOC hand. We evaluate the performance of the system in the task of ring insertion with a small clearance (0-36um). The results indicate that the robot system performs with a higher speed than a human. In fact, the average cycle time is 2.42 s for the robot, whereas it is 2.58 s for a human. The DOC hand has opened up the possibility for achieving high-speed precision assembly using robots.

The regrasping function of a robotic hand and arm has been investigated by many studies. Dynamic regrasping is performed by accelerating objects and it has the advantage of being able to perform the regrasp function at high speed. However, the difficulty of increasing the success rate is a persistent problem. In this study, we aimed to realize this continuous high-speed operation by increasing the success rate of the regrasping function. The handling of the Rubik's cube was used as the specific task to be performed. The action that was required to handle the Rubik's cube consisted of two types of regrasping motion and one type of one-face turn motion. In this study, a Rubik's cube was placed in a plane and manipulated by combining these three types of motion. Continuous operation was realized with a robotic hand and high-speed vision by utilizing environmental constraints in order to minimize the error. As a result, we succeeded 3 times in turning and regrasping in 1 s. Additionally, we were able to succeed 30 times in turning and regrasping in 10 s, with a success rate of 70%.

This paper focuses on high-performance robotic contour tracking under the uncertainties that commonly exist in actual robotic applications. These uncertainties can be attributed to the robot itself (such as modeling errors or mechanical defects like backlash) or to environmental issues (such as calibration errors or misalignment of the workpiece). We propose a non-model-based dynamic compensation approach based on the coarse-to-fine philosophy, which enables contour tracking with both high speed and good accuracy. This is achieved by adopting a methodology in which a main robot performs fast but coarse motion, while an add-on module conducts accurate compensation for the overall uncertainties using a high-speed camera and high-speed compensation actuator. An algorithm called pre-compensated proportionalderivative sliding mode control (pre-compensated PD-SMC) is proposed to control the compensation actuator. The effectiveness of the proposed contour tracking approach and control algorithm are experimentally verified using two typical planar-contour shapes: a random smooth-curvature and rectangle.

The purpose of this work is to achieve high-speed dynamic manipulation. As one example, we deal with throwing a breaking ball. In this article we deal with two types of throwing with different grasping forms. We modeled a manipulator and a ball with a sphere rolling on the tip link of a three-degrees-of-freedom manipulator in the case where a ball is thrown with spin, and with a sphere held between the tip links in the case where the ball is thrown with less spin. We simulated the motion of the ball by using these models in each case. In addition, experimental results obtained with balls thrown by a high-speed manipulator showed that the spin rates with the two types of throwing differed by a factor of 4.3 at most.

In this study, a deformation control with spatial decoupling properties is designed and implemented. This control strategy treats the shift in position and posture attributable to an external force as the deformation of the robot. The deformation dynamics are constructed from the Maxwell and Voigt models, which describe plastic and elastic deformation, respectively. Next, a control method is proposed to passively achieve different deformation characteristics in each direction. Two physical simulations with a robotic arm are executed to validate the proposed control law.

Realizing accurate robotic manipulation of flexible objects is very challenging. It asks for dexterous manipulation skill, and demands good adaptation to dynamic uncertainties due to deformation. Unlike traditional methods that basically depend on complex modeling, we follow the opposite approach by exploring possible simplifications based on high-speed motion strategy as well as high-speed visual sensing. As an application task concerned with robotic needle threading, this work demonstrates our philosophy by proposing a novel and straightforward high-speed strategy to speed up the manipulation while solves the issue of deformation uncertainty at the same time. The methodology is based on a very simple physical fact, namely that by rotating a thread with sufficient velocity, the thread can be approximated as a rigid object caused by the constantly applied centrifugal force during the rotation. Therefore, the needle threading problem is converted into a simpler peg-insertion problem, and the complexity of interaction between robot and deformable thread is significantly simplified. Based on the proposed strategy, simple technical methods then become possible for adoption to accomplish the challenging task. Experiments show that the proposed approach allows the needle threading task to be realized very rapidly.

A visually guided shock absorber for high-speed catching without rebound is designed and realized. This visual shock absorber is based on the Maxwell model, which uses plastic deformation to suppress rebounding. The shock absorber is constructed from a spring-based passive elastic body and a servo control-based software damper connected in series. The visual shock absorber is realized in a robot with two degrees of freedom and high-speed vision. The robot receives the impact of a rolling object without repelling it.

In this paper, a two-dimensional analysis of biped robot sliding dynamics is considered. First, the dynamics of a biped robot based on feet slip are derived using the Coulomb friction model. The state transition can be formulated in the centroid acceleration space whose diagram is defined as a “triangle of sliding friction.” The triangle of sliding friction's characteristics are explained by focusing on comparison with the cone of friction, which has a similar state decision diagram. Moreover, the behavioral simulation of a concrete model 2-DOF biped robot is used to analyze the sliding features in terms of the asymmetry of the dynamics of both legs.

This paper presents a visual compliance strategy to deal with the problem of fast peg-and-hole alignment with large position and attitude uncertainty. With the use of visual compliance and adoption of a light-weight 3-DOF active peg, decoupled alignment for position and attitude is realized. The active peg is capable of high-speed motion and with less dynamic defects than a traditional robot arm. Two high-speed cameras, one configured as eye-in-hand and the other as eye-to-hand are adopted to provide with the task-space feedback. Visual constraints for effecting the visual compliant motion are analyzed. Alignment experiments show that peg-and-hole alignment with the proposed approach could be successfully realized with robust convergence, and on average, the alignment could be realized within 0.7 s in our experimental setting.

This video introduces an ultra high-speed robot as a milestone in the history of intelligent manipulation systems. To develop the ultra high-speed robot under the concept of dynamics matching, we began with the development of a 1 kHz vision system. Next, we developed a sensory-motor fusion system by introducing the 1 kHz vision system. In addition, we have developed a new high-torque mini actuator and a high-speed multi-fingered hand with these incorporated. Integration of these components brings real-time dexterous manipulations unlike commonly-used control based on prediction or learning.

In this paper, dynamic horizontal movement is considered with the goal of achieving high-speed dynamic leg motion. We propose a new movement principle using frictional asymmetry for legged robots. This motion strategy consists of a sliding motion based on kinematic constraints and a jumping motion which makes use of lightweight high-torque motors. In addition, the motion characteristics based on the dynamics are analyzed. Experimental results are shown in which a 2-DOF bipedal robot takes short rapid repetitive steps with compensation for the landing time controlled by high-speed visual feedback.

In this paper, a jumping motion is considered with the goal of achieving high-speed dynamic motion for legged robots. We propose a two-step jumping pattern which makes use of the characteristic of a lightweight and fast actuator. In addition, jumping strategies based on the dynamics of the robots are presented, and the effect of structural parameter on jumping height is analyzed. Experimental results are shown in which a 1-DOF two-legged robot jumps with three patterns.

This video introduces the demonstration of skillful manipulation using a high-speed robot system. The system consists of visual and tactile sensors at a rate of 1 kHz and a high-speed hand-arm manipulator. The high-speed sensory-motor fusion improves not just the speed of existing robot manipulations, but robotic skills by introducing the features peculiar to high-speed motion. Based on such a concept, new variations of skillful manipulation were achieved.

In this paper the robotic throwing task is considered with the goal of achieving high-speed dynamic manipulation. We propose a kinetic chain approach for swing motion focused on torque transmission. In addition the release method using a robotic hand is analyzed for ball control. Experimental results are shown in which a high-speed manipulator throws a ball toward a target.

This paper describes a new realtime collision avoidance algorithm for a robot manipulator based on a new visual servo control. In the proposed algorithm, it is not necessary to compute the 3D position of the obstacle. Further, the manipulator can avoid the fast moving obstacle. The developed system uses several small light-weight high-speed vision chips placed on the surface of the robot manipulator. Experimental results of avoiding high-speed motion are shown.

In most previous studies, it has been difficult for a robot hand to regrasp a target quickly because its motion was static or quasi-static, in a constant contact state. In order to achieve high-speed regrasping, we propose a new strategy which we call dynamic regrasping. In this strategy, the regrasping task is achieved by throwing a target up and by catching it. In this paper, a regrasping strategy based on visual feedback is presented and experimental results using a high-speed multifingered robot hand and a high-speed vision system are shown. A cylinder is chosen as a specific example of target for dynamic regrasping, with which successful dynamic regrasping tasks are experimentally achieved

Speeding up robot motion provides not only improvement in operating efficiency but also improves dexterous manipulation by taking advantage of an unstable state or noncontact state. In this paper we describe a hybrid trajectory generator that produces high-speed manipulation. This algorithm produces both mechanical high-speed motion and sensor-based reactive motion. As an example of high-speed manipulation, a robotic ball control in a batting task has been achieved. Performance evaluation is also analyzed

In this paper a robotic batting algorithm using a high-speed arm and high-speed stereo vision is proposed. With this strategy, the desired trajectory of the manipulator is generated so that both high-speed swing motion and tracking motion combine to meet the ball squarely with the bat. As a result the manipulator can follow the ball while swinging the bat at high speed even if it is difficult to predict the trajectory of a ball. Experimental results are shown in which a high-speed manipulator hits a ball thrown by a human.