Kyungno Lee

KAIST interactive bicycle simulator

This paper presents key technologies and system integration issues of the KAIST interactive bicycle simulator. The rider on the bicycle feels the motion and has the visual experience as if he/she is riding in the campus of the Korea Advanced Institute of Science and Technology. The simulator consists of a bicycle, a Stewart platform, a magnetorheological handle, a pedal resistance system to generate motion feelings, a real-time visual simulator and projection system, sub-controllers and an integrating control network.

One-Wave Optical Phase Conjugation Mirror by Actively Coupling Arbitrary Light Fields into a Single-Mode Reflector

Rewinding the arrow of time via phase conjugation is an intriguing phenomenon made possible by the wave property of light. Here, we demonstrate the realization of a one-wave optical phase conjugation mirror using a spatial light modulator. An adaptable single-mode filter is created, and a phase-conjugate beam is then prepared by reverse propagation through this filter. Our method is simple, alignment free, and fast while allowing high power throughput in the time-reversed wave, which has not been simultaneously demonstrated before. Using our method, we demonstrate high throughput full-field light delivery through highly scattering biological tissue and multimode fibers, even for quantum dot fluorescence.

MIMO Output Estimation With Reduced Multirate Sampling for Real-Time Haptic Rendering

This paper presents an output-estimation method with reduced multirate sampling for real-time multi-input-multi-output (MIMO) haptic rendering. Haptic systems employ physics-based deformation models such as finite-element models and mass-spring models. These physics-based deformation models for high fidelity have to deal with complex geometries, material properties, and realistic behavior of virtual objects. This incurs heavy computational burden and time delays so that the reflective force often cannot be computed at 1 kHz which is a safe frequency for stability of the haptic systems. Lower update rates of the haptic loop and the computational time delay also deteriorate the realism of the haptic system. This problem is resolved by the proposed MIMO output-estimation method. The haptic system is designed to have two sampling times, T and JT, for the haptic loop and the graphic loop, respectively. Dynamics of the physics-based deformation is captured in a discrete and deterministic input-output model. The MIMO output estimation method is developed drawing on a least-squares algorithm and an output-error estimation model. The P-matrix resetting algorithm is also designed to deal with the changing input-output relationship of the deformation model. The parameters of the discrete input-output model are adjusted online. Intersample outputs are computed from the estimated input-output model at a high rate, and traces the correct output computed from the deformation model. This method enables graphics rendering at a lower update rate, and haptic rendering at a higher update rate. Convergence of the proposed method is proved, and performance is demonstrated through simulation with both a linear tensor-mass and a linear mass-spring models.

Multirate control of haptic interface for stability and high fidelity

This paper presents an analytic design of multirate controllers to guarantee stable haptic interaction and high fidelity. When the reflective force is computed by using slowly simulated virtual model, the control frequency of the conventional controller becomes low. This increases the zero-order-hold effect, and makes the system unstable. We propose a multirate control method to reduce the zero-order-hold effect. The multirate controller is implemented by adding a high frequency controller to the conventional controller. The high-frequency controller is designed to compensate the energy generated by the conventional controller. The stability analysis of the multirate haptic control system shows that the stiffness of the virtual model can be increased while maintaining the stability. A nonlinear virtual coupling is designed using this multirate control scheme. The multirate controller is evaluated by mathematical analysis and experiments.

KAIST interactive bicycle racing simulator: the 2nd version with advanced features

This paper presents the KAIST interactive bicycle racing simulator system, which consists of a pair of bicycle simulators. The rider on the racing simulator experiences realistic sensations of motion, while being able to see the other bicycle simulator and having the audio-visual experience of riding in a velodrome or on the KAIST campus. The 2nd bicycle of the racing simulator system consists of a bicycle, a 4-DOF platform, a handlebar and a pedal resistance system to generate motion feelings; a real-time visual simulator a HMD and beam projection system; and a 3D sound system. The system has an integrating control network with an AOIM (Area Of Interest Management) based network structure for multiple simulators.

Adjusting output-limiter for stable haptic interaction with deformable objects

This paper presents a control method using an adjusting output-limiter for stable haptic rendering in a virtual environment. In a simulation of force-reflecting interaction with deformable objects in a virtual environment, a quick computation of the accurate impedance of deformable objects is rare. This is particularly true when physics-based models, such as tensor-mass models or mass-spring models, are used. The problem is aggravated if the simulation involves changes in the geometry and/or impedance of the deformation model, such as cutting or suturing. The proposed control method guarantees stable haptic interactions with deformable objects of unknown and/or varying impedance. The method is based on the time-domain passivity theorem and the two-port network model. The controller adjusts the maximum permissible force to guarantee the passivity of the haptic system at every sampling instant. The controller notes only the magnitude of the reflective force, and does not depend on properties of the employed force model. This allows the proposed control method applicable to haptic systems involving deformable objects with unknown, nonlinear, and/or time-varying impedance. Designs of the controllers are presented for impedance-type and admittance-type haptic systems. The method is also extended for multiple degrees-of-freedom.

Real-time haptic rendering using multi-rate output-estimation with ARMAX model

This paper presents multi-rate output-estimation using an auto-regressive-moving-average with exogenous variable (ARMAX) model for real-time haptic rendering. In medical simulation, physics-based simulation of the organs and tissues including cutting and suturing is necessary for high-fidelity visual and haptic interaction. A deformation model based on a finite-element model or a mass-spring model is frequently used, which incurs heavy computational burden and time delay. Reflective force cannot be computed at 1 kHz because of the heavy computational overhead. This problem is resolved by employing a multi-rate output-estimation using ARMAX model that improves the original version of the multi-rate output-estimation with P-matrix resetting. High-fidelity reflective force is computed from the estimated input-output model at 1 kHz and the performance is evaluated with simulation.

Haptic Rendering of Drilling into Femur Bone with Graded Stiffness

This paper presents haptic rendering method of drilling into femur bone with graded stiffness. Volume rendering is preferred than surface rendering in drilling or burr simulation because the volume rendering can contain information such as density and rigidity of each voxel. However, it is difficult to implement real-time graphics and haptic rendering because of the large computational workload. Therefore, we propose surface-data-based haptic rendering of drilling process of stiffness graded material. Contact surface update and bone erosion algorithms are suggested to implement the drilling process. The proposed algorithms are adapted to the closed reduction and internal fixation surgery simulator. The proposed method allows the user of the simulation to feel the different forces according to the drilled depth.

Surface-Data-Based Haptic Rendering for Simulation of Surgery of Closed Reduction and Internal Fixation

This paper presents a surface-data-based haptic rendering method for simulation of surgery of closed reduction and internal fixation (CRIF). Volumetric data is often employed in the simulation of bone surgery because the volume rendering can easily handle information such as density and rigidity of each voxel. However, it is difficult to implement real-time graphics and haptic rendering because of the large computational workload. Therefore, we propose a surface-data- based haptic rendering method for real-time rendering. Mechanical properties and graphics of the inner part of the bone should be modeled in addition to the surface data to simulate drilling into the bone. An algorithm is developed to construct the surface of the drilled hole. This method allows the user of the simulation to feel the varying forces according to the drilled depth.

Multirate output estimation for real-time haptic rendering

This paper presents MIMO output estimation with reduced multirate sampling for real-time haptic rendering. The graphic models of the haptic systems are required to deal with complex geometries, material properties, and the dynamics of the virtual objects to display realistic deformation. Accurate graphic models often incur heavy computational burden, and the reflective force cannot be computed at 1 kHz. This problem is resolved by employing a multirate output estimation method. The dynamics of the graphic model is represented by a discrete input-output model. The parameters of the discrete input-output model are estimated on-line by the proposed multirate output estimation algorithm. The reflective force is computed from the estimated input-output model at a high rate, and traces the force computed from the graphic model as the estimation error quickly approaches zero. The convergence of the proposed estimation algorithm is proved, and the performance is evaluated with simulation