Joonbum Bae

Control of Rotary Series Elastic Actuator for Ideal Force-Mode Actuation in Human–Robot Interaction Applications

To realize ideal force control of robots that interact with a human, a very precise actuating system with zero impedance is desired. For such applications, a rotary series elastic actuator (RSEA) has been introduced recently. This paper presents the design of RSEA and the associated control algorithms. To generate joint torque as desired, a torsional spring is installed between a motor and a human joint, and the motor is controlled to produce a proper spring deflection for torque generation. When the desired torque is zero, the motor must follow the human joint motion, which requires that the friction and the inertia of the motor be compensated. The human joint and the body part impose the load on the RSEA. They interact with uncertain environments and their physical properties vary with time. In this paper, the disturbance observer (DOB) method is applied to make the RSEA precisely generate the desired torque under such time-varying conditions. Based on the nominal model preserved by the DOB, feedback and feedforward controllers are optimally designed for the desired performance, i.e., the RSEA: (1) exhibits very low impedance and (2) generates the desired torque precisely while interacting with a human. The effectiveness of the proposed design is verified by experiments.

A Compact Rotary Series Elastic Actuator for Human Assistive Systems

Precise and large torque generation, back drivability, low output impedance, and compactness of hardware are important requirements for human assistive robots. In this paper, a compact rotary series elastic actuator (cRSEA) is designed considering these requirements. To magnify the torque generated by an electric motor in the limited space of the compact device, a worm gear is utilized. However, the actual torque amplification ratio provided by the worm gear is different from the nominal speed reduction ratio due to friction, which makes the controller design challenging. In this paper, the friction effect is considered in the model of cRSEA, and a robust control algorithm is designed to precisely control the torque output in the presence of nonlinearities such as the friction. The mechanical design and dynamic model of the proposed device and the design of a robust control algorithm are discussed, and actuation performance is verified by experiments. Experimental results with a human subject are also presented to show the performance of the cRSEA while interacting with humans.

A compact rotary series elastic actuator for knee joint assistive system

Precise and large torque generation, back-drivability, low output impedance, and compactness of hardware are important requirements for human assistive robots. In this paper, a compact rotary series elastic actuator (cRSEA) is designed considering these requirements. To magnify the torque generated by an electric motor in the limited space of the compact device, a worm gear is utilized. However, the actual torque amplification ratio provided by the worm gear is different from the nominal speed reduction ratio due to friction, which makes the controller design challenging. In this paper, the friction effect is considered in the model of cRSEA, and a robust control algorithm is designed to precisely control the torque output in the presence of nonlinearities such as the friction. The mechanical design and dynamic model of the proposed device and the design of a robust control algorithm are discussed, and actuation performance is verified by experiments.

A mobile gait monitoring system for gait analysis

Conventional gait rehabilitation treatment does not provide quantitative and graphical information on abnormal gait kinematics, and the match of the intervention strategy to the underlying clinical presentation may be limited by clinical expertise and experience. In this paper, a mobile gait monitoring system (MGMS) is proposed, which helps patients self correct their gait without restriction of time and place. The proposed MGMS consists of Smart Shoes, a data acquisition board, a mobile display, and a computing system. Ground contact force (GCF) of the feet measured by Smart Shoes and the normal GCF patterns are provided as visual feedback information for patients to correct their gait by trying to follow the normal GCF pattern. The degree of gait abnormality is quantified based on how far the measured GCFs are from the normal GCF bands. Also the change of center of GCF (CoCGF) of the feet is provided as a graphical gait analysis. The performance of the proposed MGMS has been verified by preliminary trials with patients suffering from a gait disorder.

Network-Based Rehabilitation System for Improved Mobility and Tele-Rehabilitation

In this brief, a network-based rehabilitation system, which takes advantage of the Internet, wireless communication, and control, is proposed to increase the mobility of a rehabilitation system and to enable tele-rehabilitation. In the proposed system, control algorithms and rehabilitation strategies are distributed at the central location (physiotherapist) and the local site (patient) by communicating over the Internet, and the rehabilitation device is controlled wirelessly by the controller at the local site. In order to deal with possible packet losses over the local wireless network, a modified linear quadratic Gaussian controller and a disturbance observer are applied. The simulation and experimental results with an actual knee rehabilitation system show that the proposed network-based rehabilitation system can generate the desired assistive torque accurately in a network environment.

Gait phase-based smoothed sliding mode control for a rotary series elastic actuator installed on the knee joint

Actuators for physical human-robot interaction (pHRI), such as series elastic actuators, should generate the desired torque precisely. However, the resistive and inertia loads inherent in the actuators (e.g., friction, damping, and inertia) set challenges in the control of actuators in a force (torque) mode. The resistive factors include nonlinear effects and should be considered in the controller design to generate the desired force accurately. Moreover, the uncertainties in the plant dynamics make the precise torque control difficult. In this paper, nonlinear control algorithms are exploited for a rotary series elastic actuator to generate the desired torque precisely in the presence of nonlinear resistive factors and modeling uncertainty. The sliding mode control smoothed by a boundary layer is applied to enhance the robustness for the modeling uncertainty without chattering phenomenon. In this paper, the rotary series elastic actuator (RSEA) is installed on the knee joint of an orthosis, and the thickness of the boundary layer is changed by gait phases in order to minimize the torque error without the chattering phenomenon. The performance of the proposed controller is verified by experiments with actual walking motions.

Modified preview control for a wireless tracking control system with packet loss

In this paper, a modified preview control technique is proposed to compensate packet loss in a wireless tracking control system, where future reference signals over a finite horizon can be previewed. In order to utilize future reference information for the controller design, the system model is augmented with a reference generator whose states are the future reference signals. As a response to the packet loss that occurs in the wireless network, the preview control technique is modified by employing Bernoulli variables to represent packet loss in both controller-actuator and sensor-controller channels. The Bernoulli packet loss model, along with tracking errors and control inputs, is included in a quadratic cost function, and the optimal controller gain that minimizes the cost function is obtained by dynamic programming. A modified Kalman filter considering packet loss is utilized for full-state estimation and state feedback control. The choice of preview horizon is discussed and the performance of the proposed controller is verified by simulation and experimental results.

Detection of abnormalities in a human gait using smart shoes

Health monitoring systems require a means for detecting and quantifying abnormalities from measured signals. In this paper, a new method for detecting abnormalities in a human gait is proposed for an improved gait monitoring system for patients with walking problems. In the previous work, we introduced a fuzzy logic algorithm for detecting phases in a human gait based on four foot pressure sensors for each of the right and left foot. The fuzzy logic algorithm detects the gait phases smoothly and continuously, and retains all information obtained from sensors. In this paper, a higher level algorithm for detecting abnormalities in the gait phases obtained from the fuzzy logic is discussed. In the proposed algorithm, two major abnormalities are detected 1) when the sensors measure improper foot pressure patterns, and 2) when the human does not follow a natural sequence of gait phases. For mathematical realization of the algorithm, the gait phases are dealt with by a vector analysis method. The proposed detection algorithm is verified by experiments on abnormal gaits as well as normal gaits. The experiment makes use of the Smart Shoes that embeds four bladders filled with air, the pressure changes in which are detected by pressure transducers.

Kinematic Analysis of a 5-DOF Upper-Limb Exoskeleton With a Tilted and Vertically Translating Shoulder Joint

In this paper, an upper-limb exoskeleton with a tilted and vertically movable shoulder joint is proposed. By analyzing the biomechanics of the shoulder, the upper limb for the shoulder and the elbow was approximated to five degrees of freedom (DOFs) by including the vertical translation of the glenohumeral joint of the shoulder, in addition to the 3 DOFs of the shoulder and 1 DOF of the elbow, which are conventionally used to analyze the motion of the shoulder. The shoulder joint was tilted to avoid singularity problems in the workspace, i.e., by tilting the shoulder joint, the singularity position was placed outside of the normal range of motion. This configuration was analyzed using forward and inverse kinematics methods. Because the shoulder elevation affects all of the joint angles, the angles were calculated by applying an inverse kinematics method in an iterative manner. The performance of the proposed upper-limb exoskeleton and analysis methods was verified by simulations and experiments.

A network-based monitoring system for rehabilitation

Various techniques have been developed to monitor a patients motion for rehabilitation, but many of them are expensive or inadequate for monitoring motions in daily living. In this paper, a network-based monitoring system, which consists of wireless sensor modules, computers at local and remote sites connected via the Internet, and a user-friendly monitoring program, is proposed. The wireless sensor module is an array of lightweight Arduino-powered inertia measurement units (IMUs) with wireless communication powered by the ZigBee protocol. The wireless sensor modules measure kinematic information of a human body, and the measured data is analyzed at the local and host computers which are connected via the Internet. For easy observation and monitoring, a 3D human model is animated in both computers. In order to verify the performance of the proposed system, gait motions are monitored and analyzed by the proposed system with a shoe-type ground reaction force measurement system. The experimental results show that the proposed monitoring system can be used as a method to cheaply and noninvasively provide kinematic information conducive towards rehabilitation for patients, even without the presence of a trained specialist.