The design of an assistive lower limb exoskeleton robot for paraplegic patients that can measure the centre of pressure is presented. In contrast with most biped walking robots, the centre of pressure (CoP) or zero moment point (ZMP) has not been actively used in the operation of exoskeleton robots. In order to measure CoP in our exoskeleton robot, two kinds of force sensor units are installed in the exoskeleton: low profile force sensors in foot modules to measure the human weight transferred to the ground and a load cell at the shank frame to measure the supporting force. The CoP of the exoskeleton robot is calculated from the above force sensors, an inclinometer at the waist, and the positions of 14 DOF exoskeleton joints with an algorithm to change the fixed pivot using a foot contact sensor. Experiments on an able-bodied person wearing the designed exoskeleton and walking on the ground are performed to validate the designed hardware system. Through the experiments, the trajectory of the CoP of the exoskeleton with a wearer are calculated based on the proposed algorithm and it is compared with the value measured by a commercial pressure measurement system.

An exoskeleton robot helps the wearer with mechanical forces by identifying the wearer’s intentions and requires high energy efficiency, sufficient load capacity, and a comfortable fit. However, since it is difficult to implement complex anatomical movements of the human body, most exoskeleton robots are designed simply, unlike the anatomy of real humans. This forces the wearer to accept the robot’s stiffness entirely, and to use energy inefficiently from the power source. In this paper, a simple 1 degree of freedom (DoF) structure, which was mainly used in the knees of exoskeleton robots, was designed with a polycentric (multi-axial) structure to minimize the misalignment between wearer and robot, so that torque transfer could be carried out efficiently. In addition, the overall robot system was constructed by using an electro-hydraulic actuator (EHA) to solve the problems of the energy inefficiency of conventional hydraulic actuators and the low load capacity of conventional electric actuators. After the configuration of the hardware system, the sliding mode controller was designed to address the EHA nonlinear models and the uncertainty of the plant design. This was configured as Simulink for the first verification, and the experiment was conducted by applying it to the actual model to demonstrate the performance of the sliding mode control. In this process, an optical rotary encoder was used as the main feedback sensor of the controller. The proposed polycentric knee exoskeleton robot system using the EHA was able to reach the desired target value well despite the presence of many model uncertainties.

As an alternative to high-cost shoe insole pressure sensors that measure the insole pressure distribution and calculate the center of pressure (CoP), researchers developed a foot sensor with FSR sensors on the bottom of the insole. However, the calculations for the center of pressure and ground reaction force (GRF) were not sufficiently accurate because of the fundamental limitations, fixed coordinates and narrow sensing areas, which cannot cover the whole insole. To address these issues, in this paper, we describe an algorithm of virtual forces and corresponding coordinates with an artificial neural network (ANN) for low-cost flexible insole pressure measurement sensors. The proposed algorithm estimates the magnitude of the GRF and the location of the foot plantar CoP. To compose the algorithm, we divided the insole area into six areas and created six virtual forces and the corresponding coordinates. We used the ANN algorithm with the input of magnitudes of FSR sensors, 1st and 2nd derivatives of them to estimate the virtual forces and coordinates. Eight healthy males were selected for data acquisition. They performed an experiment composed of the following motions: standing with weight shifting, walking with 1 km/h and 2 km/h, squatting and getting up from a sitting position to a standing position. The ANN for estimating virtual forces and corresponding coordinates was fitted according to those data, converted to c script, and downloaded to a microcontroller for validation experiments in real time. The results showed an average RMSE the whole experiment of 31.154 N for GRF estimation and 8.07 mm for CoP calibration. The correlation coefficients of the algorithm were 0.94 for GRF, 0.92 and 0.76 for the X and Y coordinate respectively.

Lower limb exoskeleton robots help with walking movements through mechanical force, by identifying the wearer’s walking intention. When the exoskeleton robot is lightweight and comfortable to wear, the stability of walking increases, and energy can be used efficiently. However, because it is difficult to implement the complex anatomical movements of the human body, most are designed simply. Due to this, misalignment between the human and robot movement causes the wearer to feel uncomfortable, and the stability of walking is reduced. In this paper, we developed a two degrees of freedom (2DoF) ankle exoskeleton robot with a subtalar joint and a talocrural joint, applying a four-bar linkage to realize the anatomical movement of a simple 1DoF structure mainly used for ankles. However, bidirectional tendon-driven actuators (BTDAs) do not consider the difference in a length change of both cables due to dorsiflexion (DF) and plantar flexion (PF) during walking, causing misalignment. To solve this problem, a BTDA was developed by considering the length change of both cables. Cable-driven actuators and exoskeleton robot systems create uncertainty. Accordingly, adaptive control was performed with a proportional-integral-differential neural network (PIDNN) controller to minimize system uncertainty.

In the development of a wearable robot, compact volume size, high energy efficiency, and a high load capacity linear actuator system are necessary. However, conventional hydraulic actuator systems are difficult to apply to wearable robots. Also, they have nonlinearities because of the presence of hydraulic fluid in a single rod cylinder. Electric linear actuators resolve the problems of hydraulic systems. However, due to their low load capacity, they are not easy to apply to wearable robots. In this paper, a pump-controlled electro-hydraulic actuator (EHA) system that considers the disadvantages of the hydraulic actuator and electric actuator is proposed for a wearable robot. Initially, a locking circuit design is considered for the EHA to give the system load holding capacity. Based on the developed model, the adaptive sliding mode control (ASMC) scheme is designed to resolve the nonlinearity problem of changes in the dynamic system. The ASMC scheme is then modeled and verified with Simulink. In order to verify the performance of the proposed adaptive control with the model, experiments are conducted. The proposed EHA verifies that the ASMC reaches the target value well despite the existence of many model uncertainties.

Exoskeleton robots have been developed in various fields and are divided into electric and hydraulic exoskeletons according to the actuator type. In the case of hydraulic robots, because a unidirectional pump is applied, there are limitations to the wearer’s walking. In addition, robot systems are complicated, because a directional control valve is required to change the direction of the actuator. To solve these problems, we designed the electro-hydraulic actuator (EHA) system which has both the hydraulic and electric advantages. The EHA system consists of a hydraulic bidirectional pump, a motor, a hydraulic cylinder, and various valves. For the development of the piston pump, we analyzed the gait cycle and considered the flow rate and pulsation rate. In order to reduce the size and weight of the EHA system, the valves were made from one manifold, and the hydraulic circuit was simplified. We verified that the developed EHA system is applicable to robots through position and force control experiments. Because the hydraulic system is nonlinear, we designed a sliding mode control (SMC) and compared it with the proportional integral derivative (PID) controller.