Seungyong Hyung

A new adaptive frequency oscillator for gait assistance

To control exoskeletons for walking gait assistance, it is of primary importance to control them to act synchronously with the gaits of users. To effectively estimate the gait cycle (or the phase within a stride) of users, we propose a new adaptive frequency oscillator (AFO). While previous AFOs successfully estimated the walking frequency from joint angles as inputs, the new AFO, called particularly-shaped adaptive oscillator (PSAO) can estimate gait cycle from the same inputs, which would have required foot contact sensors in previous approaches. To predict the effects of PSAO-based gait assistance on human walking, it has been tested with neuromuscular walking simulation. In the simulation, the gait assistance system reduced the metabolic cost of walking for some assistance patterns. The walk ratio (step length per step rate) also changed as assistance patterns shifted in phase, which is meaningful because metabolic cost of walking in general is minimal at specific walk ratio. For a prototype exoskeleton we developed, the effect of gait assistance was experimented on a human subject walking on level ground and inclining slopes to verify the predictions from the simulation: (1) physiological cost index computed from heart rate significantly decreased indicating reduction in metabolic energy expenditure; (2) walk ratio was in fact controllable to an extent.

Modeling and control of robotic surgical platform for single-port access surgery

In this paper, we present a modeling and control method for a single-port access robot developed by our robotics group at the Samsung Advanced Institute of Technology. The surgical robot consists of a snake-like 6-degree-of-freedom (DOF) guide tube, two 7-DOF tools, a 3-DOF stereo camera, and a 5-DOF slave arm. The robot is capable of reaching various surgical sites inside the abdominal cavity from a single incision on the body. To estimate the workspace and control the guide tube to a desired location, we first obtain the forward kinematics model of the guide tube and then propose a Cartesian-level controller. The wire actuation mechanism for the tools exhibit nonlinear backlash behavior because of wire compliance and friction between the wire and Teflon-coated conduit. We compensate for the backlash in the tool joints by adding the backlash inverse with smoothing term as a feedforward term.

On-board odometry estimation for 3D vision-based SLAM of humanoid robot

This paper addresses a vision-based 3D motion estimation framework for humanoid robots, which copes with human-like walking pattern. A humanoid robot, called Roboray, is designed for dynamic walking control with heel-toe motion like a human. In spite of stability and energy efficiency of the dynamic walking, it accompanies larger swaying motion and more uncertainty in camera movement than the conventional ZMP (Zero Moment Point)-based walking does. The framework effectively uses on-board odometry information from the robot to improve the performance of the visionbased motion estimation. To accomplish this, we propose an onboard odometry filter which fuses kinematic odometry, visual odometry, and raw IMU data. And the odometry filter is combined with vision-based SLAM to provide accurate motion model, so it enhances the SLAM estimates. Experimental results in indoor environment verify that the framework can successfully estimate the pose of Roboray in real-time.

Robust descriptors for 3D point clouds using Geometric and Photometric Local Feature

The robust perception of robots is strongly needed to handle various objects skillfully. In this paper, we propose a novel approach to recognize objects and estimate their 6-DOF pose using 3D feature descriptors, called Geometric and Photometric Local Feature (GPLF). The proposed descriptors use both the geometric and photometric information of 3D point clouds from RGB-D camera and integrate those information into efficient descriptors. GPLF shows robust discriminative performance regardless of characteristics such as shapes or appearances of objects in cluttered scenes. The experimental results show how well the proposed approach classifies and identify objects. The performance of pose estimation is robust and stable enough for the robot to manipulate objects. We also compare the proposed approach with previous approaches that use partial information of objects with a representative large-scale RGB-D object dataset.

Real-time 3D simultaneous localization and map-building for a dynamic walking humanoid robot

In this paper, we develop an onboard real-time 3D visual simultaneous localization and mapping system for a dynamic walking humanoid robot. With the constraints of processing and real-time operation, the system uses a lightweight localization and mapping approach based around the well-known extended Kalman filter but that features a robust and real-time relocalization system able to allow loop-closing and robust localization in 6D. The robot is controlled by torque references at the joints using its dynamic properties. This results in more energy efficient motion but also in lager movement than the one found in a conventional ZMP-based humanoid which carefully maintains the position of the center of mass on the plane. These more agile motions pose challenges for a visual mapping system having to operate in real time. The developed system features a combination of stereo camera, robust visual descriptors, and motion model switching to compensate for the larger motion and uncertainty. We provide practical implementation details of the system and methods, and test on the real humanoid robot. We compare our results with motion obtained with a motion capture system.

Simulating gait assistance of a hip exoskeleton: Feasibility studies for ankle muscle weaknesses

This paper presents a simulation framework for pathological gait assistance with a hip exoskeleton. Previously we had developed an event-driven controller for gait assistance [1]. We now simulate (or optimize) the gait assistance in ankle pathologies (e.g., weak dorsiflexion or plantarflexion). It is done by 1) utilizing the neuromuscular walking model, 2) parameterizing assistive torques for swing and stance legs, and 3) performing dynamic optimizations that takes into account the human-robot interactive dynamics. We evaluate the energy expenditures and walking parameters for the different gait types. Results show that each gait type should have a different assistance strategy comparing with the assistance of normal gait. Although we need further studies about the pathologies, our simulation model is feasible to design the gait assistance for the ankle muscle weaknesses.

Compact Hip-Force Sensor for a Gait-Assistance Exoskeleton System

In this paper, we propose a compact force sensor system for a hip-mounted exoskeleton for seniors with difficulties in walking due to muscle weakness. It senses and monitors the delivered force and power of the exoskeleton for motion control and taking urgent safety action. Two FSR (force-sensitive resistors) sensors are used to measure the assistance force when the user is walking. The sensor system directly measures the interaction force between the exoskeleton and the lower limb of the user instead of a previously reported force-sensing method, which estimated the hip assistance force from the current of the motor and lookup tables. Furthermore, the sensor system has the advantage of generating torque in the walking-assistant actuator based on directly measuring the hip-assistance force. Thus, the gait-assistance exoskeleton system can control the delivered power and torque to the user. The force sensing structure is designed to decouple the force caused by hip motion from other directional forces to the sensor so as to only measure that force. We confirmed that the hip-assistance force could be measured with the proposed prototype compact force sensor attached to a thigh frame through an experiment with a real system.