Changmook Chun

Particle filtering on the Euclidean group: framework and applications

We address general filtering problems on the Euclidean group SE(3). We first generalize, to stochastic nonlinear systems evolving on SE(3), the particle filter of Liu and West for simultaneous estimation of the state and covariance. The filter is constructed in a coordinate-invariant way, and explicitly takes into account the geometry of SE(3) and P(n), the space of symmetric positive definite matrices. Some basic results for bilinear systems on SE(3) with linear and quadratic measurements are also derived. Three examples—GPS attitude estimation, needle tip location, and vision-based robot end-effector pose estimation—are presented to illustrate the framework.

Development of a Slim Haptic Glove Using McKibben Artificial Muscles

In this paper, a light-weight and wearable haptic glove system is introduced which is designed for virtual environments. In order to reduce the weight of the system, micro McKibben artificial muscles are used and 2-port solenoid valve pneumatic system was developed for faster response. Hydraulic system was also developed to actuate artificial muscles, so that we can overcome softness and inaccuracy of pneumatic system due to the compressibility of air. We verify the functionality and usefulness of the proposed system by synchronizing it with a virtual environment

Autonomous Navigation of KUVE (KIST Unmanned Vehicle Electric)

This article describes the system architecture of KUVE (KIST Unmanned Vehicle Electric) and unmanned autonomous navigation of it in KIST. KUVE, which is an electric light-duty vehicle, is equipped with two laser range finders, a vision camera, a differential GPS system, an inertial measurement unit, odometers, and control computers for autonomous navigation. KUVE estimates and tracks the boundary of road such as curb and line using a laser range finder and a vision camera. It follows predetermined trajectory if there is no detectable boundary of road using the DGPS, IMU, and odometers. KUVE has over 80% of success rate of autonomous navigation in KIST.

Effect of Focal Muscle Vibration on Calf Muscle Spasticity: A Proof-of-Concept Study

Focal vibration has been studied for its ability to reduce spasticity in patients with upper motor neuron lesions, but adequate stimulation parameters remain unclear. Focal muscle vibration with adequate parameters may facilitate gait rehabilitation in patients with lower limb spasticity.

Micro hydraulic system using slim artificial muscles for a wearable haptic glove

Over the past few decades, various haptic gloves have been developed for use in virtual environments. The actuating systems for most existing haptic gloves require lots of external auxiliary equipment. Because of this, the motion of the user is restricted by the length of the electric wires or pneumatic tubes attached to this equipment. A compact actuation system, including related equipment, is thus indispensable for a wearable haptic glove to be truly effective. To resolve the problem of hampered motion and reach, a micro hydraulic actuating system was developed in this research. It was composed of a slim, flexible artificial muscle, a compact hydraulic module for actuating the muscle, and a micro pressure sensor for measuring without flux loss. The characteristics of the muscle were investigated for their control capacity. The step and sinusoidal responses were analyzed to evaluate the performance of the micro hydraulic system. Once these analyses were completed, a lightweight and compact actuation system was built incorporating a wearable haptic glove. By virtue of the developed micro hydraulic system, the wearable haptic glove was able to operate independently of any external equipment, and movement was completely free of any restrictions from wires or tubes.

Sensor fusion-based line detection for unmanned navigation

We propose an algorithm of reliable detection of line for unmanned navigation of mobile robots using sensor fusion. To detect the distance and the angle between the robot and the line, we use a vision sensor system and a laser range finder (LRF). Each sensor system runs its own extended Kalman filter (EKF) to estimate the distance and orientation of the line. The vision system processes images being captured using well-known edge detection algorithms, and the LRF detects the line using the measurement of the intensity of the laser beam reflected. However, depending on the condition of the road and ambient light, each sensor gives us wrong measurement of the line or sometimes completely fails to detect it. To resolve such uncertainty, we develop a simple and easy-to-implement sensor fusion algorithm that uses weighted sum of the output of each EKF, and it gives us more reliable estimate of the distance and orientation of the line than each measurement/estimator system.

Bezier Curve-Based Path Planning for Robust Waypoint Navigation of Unmanned Ground Vehicle

This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.

Particle Filtering on the Euclidean Group

We address general filtering problems on the Euclidean group SE(3). We first generalize, to stochastic nonlinear systems evolving on SE(3)9 the particle filter of Liu and West (2001) for simultaneously estimating the state and covariance. The filter is constructed in a coordinate-invariant way, and explicitly takes into account the geometry of SE(3) and P(n)9 the space of symmetric positive definite matrices. An experimental case study involving vision-based robot end-effector pose estimation is also presented.

Gaussian process learning and interpolation of gait motion for rehabilitation robots

We present an alternative approach to generate gait motion at arbitrary speed for gait rehabilitation robots. The methodology utilizes Gaussian process dynamical model (GPDM), which is a nonlinear dimensionality reduction technique. GPDM consists of a dynamics in low-dimensional latent space and a mapping from the space to configuration space, and GPDM learning results in the low-dimensional representation of training data and parameters for the dynamics and mapping. We use second-order Markov process dynamics model, and hence given a pair of initial points, the dynamics generates a latent trajectory at arbitrary speed. We use linear regression to obtain the initial points. Mapping from the latent to configuration spaces constructs trajectories of walking motion. We verify the algorithm with motion capture data from 50 healthy subjects, who walked on a treadmill at 1, 2, and 3 km/h. We show examples and compare the original and interpolated trajectories to prove the efficacy of the algorithm.

Evaluating the Differential Electrophysiological Effects of the Focal Vibrator on the Tendon and Muscle Belly in Healthy People

Objective To investigate the electrophysiological effects of focal vibration on the tendon and muscle belly in healthy people. Methods The miniaturized focal vibrator consisted of an unbalanced mass rotating offset and wireless controller. The parameters of vibratory stimulation were adjusted on a flat rigid surface as 65 µm at 70 Hz. Two consecutive tests on the different vibration sites were conducted in 10 healthy volunteers (test 1, the Achilles tendon; test 2, the muscle belly on the medial head of the gastrocnemius). The Hoffman (H)-reflex was measured 7 times during each test. The minimal H-reflex latency, maximal amplitude of H-reflex (Hmax), and maximal amplitude of the M-response (Mmax) were acquired. The ratio of Hmax and Mmax (HMR) and the vibratory inhibition index (VII: the ratio of the Hmax after vibration and Hmax before vibration) were calculated. The changes in parameters according to the time and site of stimulation were analyzed using the generalized estimating equation methods. Results All subjects completed the two tests without serious adverse effects. The minimal H-reflex latency did not show significant changes over time (Wald test: χ2=11.62, p=0.07), and between the two sites (χ2=0.42, p=0.52). The changes in Hmax (χ2=53.74, p<0.01), HMR (χ2=20.49, p<0.01), and VII (χ2=13.16, p=0.02) were significant over time with the adjustment of sites. These parameters were reduced at all time points compared to the baseline, but the decrements reverted instantly after the cessation of stimulation. When adjusted over time, a 1.99-mV decrease in the Hmax (χ2=4.02, p=0.04) and a 9.02% decrease in the VII (χ2=4.54, p=0.03) were observed when the muscle belly was vibrated compared to the tendon. Conclusion The differential electrophysiological effects of focal vibration were verified. The muscle belly may be the more effective site for reducing the H-reflex compared to the tendon. This study provides the neurophysiological basis for a selective and safe rehabilitation program for spasticity management with focal vibration.