Subspace predictive control (SPC) is a data-driven control strategy that utilizes input–output measurements to predict future system behavior without requiring explicit model identification. Conventional SPC exhibits vulnerability to an unknown input disturbance, leading to degraded control performance and steady-state errors. To address these limitations, this article proposes a robust SPC method that inherently mitigates the effect of a constant input disturbance by augmenting the state-space representation through the internal model principle (IMP). This augmentation enables the controller to achieve integral action without requiring a separate disturbance observer (DOB) design. The proposed method is implemented in a data-driven framework, where an auxiliary disturbance is introduced into the data-driven algorithm to enhance disturbance rejection. A transfer function analysis verifies that the proposed Robust SPC eliminates a constant disturbance while maintaining the role of a DOB. Experimental validation on a two-inertia system confirms that the proposed method significantly improves reference tracking performance compared to conventional SPC, demonstrating its effectiveness in disturbance rejection without additional modeling complexity.

We present CityCondBERT, a Transformer for human mobility prediction in the HuMob Challenge at SIGSPATIAL GISCUP 2025. Our model integrates multi-feature spatiotemporal embeddings with city-conditioned modules (FiLM) to enable effective cross-city transfer. To reflect the sequence-level properties rewarded by GEO-BLEU, we propose a differentiable GEO-BLEU-Sinkhorn loss and employ a two-stage strategy of pooled pretraining and city-wise fine-tuning. CityCondBERT improves GEO-BLEU by approximately 25% over per-city BERT baselines trained from scratch, achieving a GEO-BLEU of 0.1516 on the organizers' evaluation split. These results highlight the effectiveness of city conditioning and our proposed sequence-aware loss in enabling robust and generalizable mobility prediction. Source code is available at https://github.com/OHSEHOON99/CityCondBERT/.

This study proposes a novel approach for low-impedance rendering in robots to ensure safe human-robot interaction. Low-impedance control enhances safety by enabling robots to respond flexibly to physical contact with humans. However, real-world disturbances such as friction often necessitate high impedance, creating a trade-off between safety and task precision. To address this challenge, a modified disturbance observer (DOB)-based control framework is introduced, designed to prevent external contact forces from being treated as disturbances. Experimental results demonstrate significant improvements in impedance rendering performance under various conditions, ensuring precise and safe robot operations in dynamic shared environments.

This paper presents a robust control algorithm for precise orientation control of robot manipulators using a disturbance observer (DOB) specifically designed for orientation dynamics. Our approach addresses the challenges of 3D orientation control by incorporating various orientation representations, such as Euler angles, quaternions, and exponential coordinates, and analyzing their impact on DOB performance. Through theoretical analysis and experimental validation, we demonstrate the effectiveness of our method in achieving high-precision orientation control under uncertainties and disturbances. This work offers a comprehensive framework for robust orientation control, advancing the application of DOB in complex robotic tasks.

Accurate driving force estimation is critical for ground vehicles operating in soft-soil terrains, where complex wheel–soil interactions involving sinkage and shear effects significantly affect vehicle mobility. Conventional Driving Force Observers (DFOs), initially developed for rigid road conditions, fail to account for these terrain-specific nonlinearities, leading to estimation offset and substantial errors. To overcome this limitation, this paper proposes a Terramechanics-Enhanced Wheel Dynamics (TEWD) model that explicitly integrates soil resistance derived from established wheel–soil interaction models. Based on the TEWD model, we develop a new driving force observer, termed TEWD-DFO, that estimates driving forces solely from internal vehicle signals without requiring additional external force sensors. The proposed method is validated through simulations conducted in the ProjectChrono environment under soft-soil conditions. Simulation results demonstrate that the TEWD-DFO significantly reduces estimation offsets and achieves robust driving force estimation performance, indicating its potential applicability in enhancing vehicle stability and control accuracy in realistic soft-soil scenarios.

Accurate dynamics modeling is crucial for achieving precise Ground Reaction Force (GRF) control and high-performance legged locomotion. However, real-world legged systems exhibit strong frictional effects with hysteresis and inter-joint coupling, which conventional static friction models or purely data-driven approaches often fail to capture. In this paper, we propose Mysteric-Net, a novel MIMO hysteretic friction-aware network that combines a Lagrangian-based formulation with a Temporal Convolutional Network (TCN). By embedding the physical laws of Lagrangian mechanics while modeling history-dependent frictional dissipation via the TCN, our framework accurately identifies the system dynamics, including complex friction and coupling effects. This paper demonstrates that the proposed method significantly improves the accuracy of inverse dynamics estimation on a robotic leg. Furthermore, this paper shows that the learned model enables the design of an effective feedforward controller that mitigates friction and enhances tracking performance over conventional baseline methods.

Robotic gantry stages are a prevalent class of industrial robots used for precise positioning tasks in various fields, including semiconductor manufacturing, 3D printing, and automated assembly. However, these systems often exhibit time-varying dynamics because the position of the end-effector (i.e., the payload) shifts the mass/inertia properties. Such dynamic variations are not captured by conventional Linear Time-Invariant (LTI) models, leading to modeling inaccuracies and degraded control performance. Linear Parameter-Varying (LPV) system identification is a more suitable alternative, but existing approaches typically employ a single, fixed basis-function order for all parameters, resulting in excessive model complexity and poor efficiency.This paper presents a novel global LPV system identification method for multi-axis robotic gantry systems, enabling independent basis-function order selection for each parameter. By eliminating unnecessary high-order terms, the method reduces computational overhead and enhances modeling accuracy. Experimental validation on an industrial gantry testbed confirms superior precision and robustness compared to conventional LPV approaches with uniform polynomial orders.

Control techniques like MPC can realize contact-rich manipulation which exploits dynamic information, maintaining friction limits and safety constraints. However, contact geometry and dynamics are required to be known. This information is often extracted from CAD, limiting scalability and the ability to handle tasks with varying geometry. To reduce the need for a priori models, we propose a framework for estimating contact models online based on torque and position measurements. To do this, compliant contact models are used, connected in parallel to model multi-point contact and constraints such as a hinge. They are parameterized to be differentiable with respect to all of their parameters (rest position, stiffness, contact location), allowing the coupled robot/environment dynamics to be linearized or efficiently used in gradient-based optimization. These models are then applied for: offline gradient-based parameter fitting, online estimation via an extended Kalman filter, and online gradient-based MPC. The proposed approach is validated on two robots, showing the efficacy of sensorless contact estimation and the effects of online estimation on MPC performance. Video results can be seen at https://youtu.be/CuCTcmn3H-o.

This paper proposes an optimal design methodology for Parallel Elastic Actuators (PEAs) that minimizes torque and power consumption for tasks with external conditions. Furthermore, the paper advocates for selecting an actuator based on a comparison of the dynamic characteristics of PEAs and Series Elastic Actuators (SEAs) for a specific task. However, the design of actuators may need to vary depending on the task and application, but the criteria for this are often unclear. To address the ambiguous design criteria, we analyze the dynamic characteristics of PEAs and SEAs under external conditions and utilize them for optimal design. By formulating cost functions for various tasks, we identify the most suitable actuator design for each task. This study establishes criteria for designing PEAs for tasks with external conditions and proposes a general framework for PEA design optimization.

This paper presents a novel, nonlinearity robust identification method for deriving the inertia matrix of multi-DOF Flexible Joint Robots (FJR), utilizing resonance and anti-resonance frequencies in the Frequency Response Functions (FRF). Our proposed method overcomes the limitations of conventional approaches, which are susceptible to mechanical nonlinearities, leading to inaccurate models. By leveraging frequency domain techniques, our approach effectively mitigates the influence of nonlinear characteristics, providing a more accurate and reliable means of robot control. Furturmore, the paper highlights the benefits of frequency domain system identification, including nonlinear robustness and the ability to decompose the flexible joint into motor and load components. Finally, a novel sequential excitation algorithm is proposed to obtain the inertia matrix of a multi-DOF robot manipulator without relying on complex theories or optimizations. The effectiveness of the proposed algorithm is verified through simulation and experiment.

Recent research on quadruped robots has been achieving high-performance motion control based on optimization and reinforcement learning (RL). However, there is still ongoing research aimed at demonstrating that implementing high-performance motion based on simple and dominant dynamic principles is possible. In this paper, we proposed a novel control approach that projects Spring-Loaded Inverted Pendulum (SLIP) dynamics to articulated legs, utilizing admittance control based force observer within a rotating workspace (RWFOB). Unlike other legged robots that depend on sensor-based estimation of external forces, the proposed method presents an alternative approach that reduces the reliance on sensors. Additionally, we introduce a comprehensive control framework for quadruped robot motion control, establishing the connection between trunk and SLIP-realized leg movements using Jacobian. Through comparative analysis with Virtual Model Control (VMC) in simulations, we illustrate the effectiveness of the proposed framework as a robust and reliable trunk feedback controller.

Industrial robots have increased payload, repeatability, and reach compared to collaborative robots, however, they have a fixed position controller and low intrinsic admittance. This makes realizing safe contact challenging due to large contact force overshoots in contact transitions and contact instability when the environment and robot dynamics are coupled. To improve safe contact on industrial robots, we propose an admittance controller with inverse model compensation, designed and implemented outside the position controller. By including both the inner loop and outer loop dynamics in its design, the proposed method achieves expanded admittance in terms of increasing both gain and cutoff frequency of the desired admittance. Results from theoretical analyses and experiments on a commercial industrial robot show that the proposed method improves rendering of the desired admittance while maintaining contact stability. We further validate this by conducting actual assembly tasks of plug insertion with fine positioning, switch insertion onto the rail, and colliding the robot end effector with random objects and surfaces, as seen at https://youtu.be/8XfkdHEdWDs.

Admittance and impedance controllers are often purely feedforward, using measured external force or motion, respectively, to generate a reference for an inner-loop controller. In this case, the range of dynamics which can be rendered is limited by the inner-loop, which causes, e.g. contact stability issues for low admittance industrial robots in stiff contact. When both position and force are measured, feedback control can be added to more flexibly reshape the rendered dynamics. This paper uses velocity feedback to increase the admittance of motion-controlled industrial robots in force control applications. This allows an industrial robot with a lower intrinsic admittance, which may be needed for payload, speed, or accuracy, to realize a higher admittance by control, allowing lighter manual guidance and safer contact. This is achieved by a modified disturbance observer, where an inverse dynamic model estimates external forces and amplifies them with positive feedback. This approach is compared with using positive velocity feedback with a shaping filter. Here, velocity reference calculated by the virtual admittance model is modified by the DOB (Dist-Add) or the positive velocity feedback (Vel-Add). When combined with an outer-loop admittance controller, these methods can render a higher admittance while maintaining contact stability compared to standard feedforward admittance control.

A Multi-Input-Multi-Output (MIMO) system has complex interactions between inputs and outputs, resulting in a coupling effect that can lead to undesired motions. To effectively control MIMO systems, decoupling is necessary. This paper introduces a decoupling method that uses a transformation matrix modeled as a transfer function using Frequency Response Function (FRF). Unlike the conventional decoupling method uses constant transformation matrix obtained through Canonical Polyadic Decomposition (CPD) and shows performance degradation in certain frequency bands, the proposed method creates transformation matrix as a transfer function and demonstrates better decoupling performance across the entire frequency band. The performance of the proposed method is validated through simulations on a hybrid dual-drive gantry stage.

The use of impedance control has become widespread in applications requiring simultaneous position tracking and compliance in contact. However, disturbances such as friction and model uncertainties can adversely affect the performance of impedance-based motion control. The disturbance observer (DOB) has been proposed to address this issue, which is a widely-utilized robust controller that eliminates observed disturbances with the nominal model. However, current DOB applications fail to consider the aspect of interactive force control properly. This study proposes a novel Workspace Force/Acceleration Disturbance Observer (WFADOB) controller, which utilizes both interaction force and acceleration to design a disturbance observer loop, enabling precise motion tracking even with low-impedance gain settings. Additionally, the proposed controller offers fine impedance rendering performance, offering safe contact while maintaining low impedance. This paper discusses the problem of motion tracking performance due to friction and the interaction force that arises during contact. The proposed controller is theoretically analyzed and experimentally verified, demonstrating its performance compared to conventional methods.

In this paper, the parametric identification is addressed by a kernel-based model with covariance and a novel model order selection algorithm. The kernel-based model is uti-lized for training the sampled frequency response characteristics, which is insufficient for parametric identification because of noisy and discrete data. The kernel-based frequency response model improves the parametric identification by using the high covariance data. In addition, prior knowledge of the model order is essential for parametric identification. This paper proposes a novel model order selection based on the robust stability criterion of disturbance observer (DOB). The effectiveness of the proposed algorithm is verified through numerical simulations under several conditions.

Upper limb exoskeleton robots have been widely used to assist humans in industry and rehabilitation. Human-robot interaction control consists of two modes. A compliant mode and an assistive mode. The compliant mode is manipulating the robot compliantly according to the movement of the human. At this time, the human must not receive impedance from the robot. Therefore, in this paper, a novel external force control which makes the robot follow human movement without causing resistance is proposed. The assistive mode is to generate assistive power according to human intention. In this paper, the algorithm for recognizing the human intention for primitive movement and generating assistive forces adaptive to real-time work environments is proposed. The proposed two modes are also integrated into a novel human-robot interaction control framework. The performance of the proposed methods is verified through experiments.

Safe physical interaction using admittance control on an industrial robot with inner-loop motion control remains challenging. This is partly due to the low intrinsic admittance and stability issues from inner-loop motion control limitations (e.g. bandwidth). To increase the admittance at an interaction point with the user/environment, this paper proposes a robust admittance control architecture. A disturbance observer (DOB) is used to improve effective inner-loop motion control, suppressing the effects of velocity disturbances. The DOB uses the robot's closed-loop task space velocity control as the nominal model, compensating disturbances between the commanded robot velocity and realized robot velocity output. An admittance controller uses measured force to generate robot velocity commands. Detailed analyses are carried out to theoretically evaluate the proposed control system. Experiments conducted on a COMAU RACER-7-1.4 industrial robot verify the effectiveness of the proposed admittance control scheme and stability in environmental contact. Moreover, the proposed method is simple to implement on the existing robot system.

This paper presents a comprehensive comparative study of the multisensor-based force observers for accurate force control. A force controlled system which contains a force sensor for measuring force transmitted to the load by the motor and an encoder for measuring motor position is considered as the general multisensor-based motion system in this study. Even though these multisensor-based motion systems are emerging as potential motion systems as the demands for collaborative robots increase, there has been few studies that investigate their advantages and limitations. to address this issue, three types of observer-based force controllers that utilize the multisensors are designed and implemented. These controllers exploit the availability of force sensor, motor encoder, and motor torque information from the multisensor-based motion system to estimate accurate force which is later utilized to close the feedback loop. Mathematical and quantitative analyses are conducted to compare performances of the proposed observer-based force control and through this, their advantages and limitations are pointed out. Finally, simulation and an experimental case study with an actual robot are conducted to validate the force tracking performance of the designed force control systems.

In this study, a novel mobile robot that can throw precisely a stone in a curling match is introduced. This mobile robot plays alongside a human team. Several requirements for developing the mobile robot are defined so that it follows the game rules and operates on an ice field. A static force analysis considering the operating conditions of the mobile robot is conducted to derive the required motor torque and the optimal mechanical design. For a successful stone-throwing, the mobile robot must present a high driving performance on an ice surface with a target velocity and an angle provided by an autonomous strategy generator. To achieve the target velocity on an icy surface, a velocity control algorithm based on slip ratio control (SRC) is proposed. Moreover, to precisely achieve heading angle control, a heading angle controller including a steering angle disturbance observer (SA-DOB) is introduced. The mathematical model of the SA-DOB is derived by a dynamic analysis of the mobile robot. Several experimental results verify the proposed motion control algorithm and the feasibility of the mobile robot as a curling robot to compete with a human team. This study is motivated by the challenge of driving a mobile robot on an extremely slippery surface with high-accuracy motion for curling. To prevent slippage, a slip ratio controller is adopted based on the difference between the wheel and robot speeds. To maintain a desired heading angle of the mobile robot during driving, orientation control based on the yaw dynamics is developed. Moreover, the robot does not require any positioning information from external sources, such as sensors and cameras. In addition to playing an actual game, this curling robot can be utilized for training athletes. Furthermore, the developed algorithms for high-accuracy driving on ice in an indoor stadium can be applied to various mobile robots that drive on other slippery environments (such as sand and dust) and sealed spaces (such as underground warehouses) where external positioning signals cannot be received. The proposed robot is limited to straight driving, and the possibility of extending it to circular motion is still under development. Note to Practitioners—This study is motivated by the challenge of driving a mobile robot on an extremely slippery surface with high-accuracy motion for curling. To prevent slippage, a slip ratio controller is adopted based on the difference between the wheel and robot speeds. To maintain a desired heading angle of the mobile robot during driving, orientation control based on the yaw dynamics is developed. Moreover, the robot does not require any positioning information from external sources, such as sensors and cameras. In addition to playing an actual game, this curling robot can be utilized for training athletes. Furthermore, the developed algorithms for high-accuracy driving on ice in an indoor stadium can be applied to various mobile robots that drive on other slippery environments (such as sand and dust) and sealed spaces (such as underground warehouses) where external positioning signals cannot be received. The proposed robot is limited to straight driving, and the possibility of extending it to circular motion is still under development.

This article proposes a new data-driven optimization of integrated control for flexible systems to achieve high-performance automatic control. The integrated control that is composed of feedback control, feedforward control, and disturbance observer is adopted in this article as the control framework that can effectively address the control problems of the flexible system. However, it is difficult to optimize all the parameters of the integrated control, because the number of the parameters to be optimized is larger than the conventional feedback control, which complicates the optimization procedure. In this article, the optimization procedure of the integrated control as well as the mathematical background of it is proposed. At first, the closed-loop characteristics of the integrated control are analyzed and its convexity with respect to control parameters is theoretically investigated. The proposed optimization method is designed taking into consideration the convexity of the control configuration to guarantee the global optimality of the obtained parameters. Moreover, the proposed method can simultaneously optimize all the parameters of the integrated controller based on the experimental data. The effectiveness of the proposed algorithm is experimentally confirmed using a flexible system under the following two conditions: first, change of initial parameters and second, change of plant conditions.

Three-wheeled electric mobility is an effective means of transport in a small and narrow space. As this electric mobility is widely utilized, the request of safety and performance for this mobility has become important. And thus a fault tolerance function needs to be developed to minimize the user’s intervention and improve driving performance. Fault-tolerance technology is applied mainly to sensors, but a fault tolerance function is also required from the viewpoint of driving-related actuators.In this paper, a fault tolerance algorithm is proposed taking use of newly-proposed concept steering fault disturbance and Model Predictive Control (MPC).To this end, an index is proposed to represent the failure of the steering motor as an objective numerical value, and this index is used for the driving controller of electric mobility.In this driving controller, MPC is designed based on a dynamic model of three-wheeled electric mobility to regulate the input values of steering angle and yaw moment to maintain driving performance by referring to the proposed index.By using the proposed algorithm based on the MPC, electric mobility can drive along a given route without user’s intervention in the event of a breakdown. The proposed fault tolerance algorithm is verified through various driving scenarios using a simulation model that reflects three-wheeled electric mobility.

Instability which occurs when the robot’s end effector contacts a very stiff environment is a challenge in designing control systems for safe physical interaction and cooperation of robots with environment. One of the reasons for the instability is force disturbances caused by the mechanical factors of the robot system. To this effect, this paper presents the design, analysis, and implementation of a robust impedance controller for a force servo system. To suppress the force disturbances, a force disturbance observer (FDOB) is implemented in the impedance-controlled system. For comparison purposes, impedance control system when the FDOB is not implemented is also designed and analyzed. Further, using the passivity approach, coupled stability conditions of the designed impedance control systems are derived and analyzed to assess the effect of FDOB on passivity and overall control performance. Simulations and experiments are conducted to evaluate performance of the designed impedance control systems and it is found that the FDOB-based control system shows superior performance by improving contact stability compared to direct force sensor feedback control system.

Legged robots have opened their way to more stable and practical mobile robot applications. However, their locomotion strategies are limited to similar patterns, and dynamic running at high speed still is not successfully realized. One of the key technology required for the realization of the dynamic running of the legged robot is to estimate the ground contact force and control it in real-time. This paper tackles this problem in two ways: the derivation of the observer algorithm based on the leg dynamics and the simplification of the observer design using the Rotating Workspace motion description. To this end, two novel coordinate systems are introduced to describe the joint space motion and the workspace differently, and the ground contact force observer is designed in the novel coordinate systems. The performance of the proposed observer is verified through experimental results.

In many series-elastic actuator applications, the ability to safely render a wide range of impedance is important. Advanced torque control techniques such as the disturbance observer (DOB) can improve torque tracking performance, but their impact on safe impedance range is not established. Here, safety is defined with load port passivity, and passivity conditions are developed for two variants of DOB torque control. These conditions are used to determine the maximum safe stiffness and Z-region of the DOB controllers, which are analyzed and compared with the no DOB case. A feedforward controller is proposed which increases the maximum safe stiffness of the DOB approaches. The results are experimentally validated by manual excitation and in a high-stiffness environment.

Low frequency dynamic force offsets and measurement noises make utilization of force sensor signal a difficult task, especially, the direct feedback of force measurements in force control systems. To solve these force sensor problems, a novel Kalman filter-based force observer that automatically estimates and eliminates force sensor offsets and attenuates measurement noises is developed in this paper. A dynamic model of force sensing system is derived taking into consideration the dynamic interaction among the motor, the load, and the force sensor between them, as well as the measurement equations. The state-space representation of dynamic force offsets is formulated and augmented to the system dynamic equations from which a state-space Kalman filter is designed. The properties of the designed Kalman filter are further theoretically analyzed in the transfer function form. To verify its effectiveness, experiments are carried out where performance comparison is made to that of a conventional Kalman filter. The proposed observer is found to perform better than the conventional one. Moreover, the transfer function form exhibits a simple structure which makes it simple to implement.

The side-slip angle is an important motion state for stable driving in mobile platform, and commercial sensors for the side-slip angle measurement are expensive. In this paper, a side-slip angle estimator is introduced to be utilized in the sweeping robot. Curling robot consist of several mobile robots which includes the sweeping robot as well as skip robot and throwing robot. To estimate the side-slip angle, a state observer is developed which requires the lateral force calculated by using the steering moment of the sweeping robot. Considering the mechanical structure of the sweeping robot, the principle of bending moment analysis with the nodal hinged constrain beam is applied to define the relationship between the lateral force and steering moment. This approach is different with the conventional method which is based on the cornering stiffness and the direct lateral force sensor measurement. Furthermore, the lateral velocity, which is obtained from the camera attached in the skip robot, is also utilized in the state observer-based estimator. The simulation and experimental results prove the defined relationship between lateral force and the steering moment and verify the proposed estimation algorithm.

This paper proposes a novel switch control for the series elastic actuator (SEA). This switch control provides more robust position control along with better impulse dissipation performance. SEA is an actuator technology commonly used in robotic applications that require safe and precise interaction control. The SEA has built-in spring elements to inherently measure or estimate the transmitted force. It is often used for the application where the relevant action between motion and force is needed. The switching problem between position and torque control is one of the major issues, especially in situations where both position and torque information are critical, such as collisions. To deal with this problem, we discuss the conventional switching method and suggest a new method. Besides, this paper describes the criteria for comparing and analyzing them and presents a new approach that utilizes the concept of power to evaluate the performance of switching algorithms.

This paper proposes a novel control system using a Series Elastic Actuator (SEA) for human-machine interactive applications. SEA allows high torque transparency between a forward and a backward torque transmission with the geared motor and the closed-loop controller and it so enables that human-friendly interaction is achieved. Even though the torque-controlled SEA system plays important roles in human-machine interactive applications, there is performance limitation to implement pure interactive behavior due to the imperfection of torque source such as torque ripple of the electric motor. The limitation of SEA causes the uncomfortable feeling to the human in the application such as steer-by-wire system which is the target system in this paper. This paper focuses on the minimization of the influence that is caused by the torque ripple of the electric motor in the SEA system. The proposed controller based on the principle of Disturbance Observer (DOB) is designed to realize the desired human-machine interactive behavior. Experiments have been conducted to explore the characteristics of SEA system and to verify the performance of the proposed controller.

This paper proposes a practical and less conservative passivity analysis for series elastic actuators (SEAs) by introducing load port definition and shows that the achievable stiffness by the impedance control of SEA can be set higher than the inherent stiffness of SEA depending on the condition of the load dynamics. Since SEA can inherently measure or estimate a transmitted force thanks to its embedded spring element, impedance control is often exploited to render compliant behaviors related between the motion and the force. Although the stability of the SEA control system is of great importance, the conventional passivity analysis gives conservative criteria, and indeed limits the actual actuator performance. To tackle the conservatism of the conventional passivity in SEAs, we first explore the dynamic characteristics of SEA including load dynamics, which has been ignored for the sake of simplicity of the passivity analysis by excluding uncertain load dynamics. The inclusion of the load dynamics into the passivity analysis allows us to properly derive the less conservative limit of achievable stiffness by impedance control and the factors that determine the limit. The proposed analysis is verified by numerical simulations and applied to a passivity observer design for experimental validation on an actual SEA setup.

This paper proposes a novel parallel robot - Virtual Ground Robot (VGR) - that is driven by three Series Elastic Actuators (SEAs) to interact with a human. The proposed Virtual Ground Robot provides a virtual ground on which a human can stand on and interact in three directions: the pitch, the roll and the height directions. The most significant features of the proposed VGR are that 1) it is driven by RFSEAs (Reaction Force-sensing Series Elastic Actuator), and thus it can provide precise forces and torques, 2) the size of the VGR is small enough for a human to stand on with ease, and 3) it can generate torque/force large to support a weight of a human. Taking advantage of RFSEAs utilized in the proposed VGR, Spatial Force control algorithm is proposed in this paper. In order to design this controller, the motions of VGR are defined in the task space, the joint space and the RFSEA level. Based on the Kinematics, force control of VGR in the task level, which is named Spatial Force Control is designed and verified using experiments.

With increasing of the needs to collaborate with humans throughout the industry fields, a series elastic actua-tor(SEA)has been developed which enable more compliance motion rather than conventional motor-based actuator. The device is equipped with spring inside, and it turns increased mechanical elasticity, allowing to react more flexibly to the external force, generated by external environments such as impact. In this point, it is important to measure well spring deflection. Encoder with a delivery mechanism such as the belts, the gear, and the wire is typically used for the purpose. The high-resolution encoder improves the performance of SEA, however, at the same time, it is expensive. To solve this problem, we proposed an estimating method for external force using acceleration sensor. In previous studies, external force observer using encoders were designed as a shape of the transfer function and state space. The performance of observer using acceleration sensor is compared to two previous algorithms.

Linear motors with large thrust and position accuracy have been used in a variety of industrial robot applications. Despite the advantages of the linear motor, precise control of the linear motor has been a challenging issue due to the cogging force of the linear motor. There have been many studies aimed at rejecting the unwanted cogging force of these linear motors. In this paper, a peak filter and a frequency estimation method are used to reduce the speed ripple of a linear motor. To do this, the peak filter design parameters are investigated and the performance of the frequency estimation technique for the peak filter is verified.

In this paper, a novel mobile robot developed to perform Curling sports is introduced. The developed robot is a Stone Throwing Robot (STR) for Curling that can travel on the ice with wheels and throw a stone as well as make curls of the stone. The STR is developed as a robot component of an Artificial Intelligence(AI) system that can autonomously play the curling sport. The proposed STR can throw a stone at any desired speed and in any desired direction, which are determined by the AI system. To achieve this precise driving of the STR and throwing of the stone, two dimensional drive control is developed for the STR, which consists of 1) anti-slip control for high traction, 2) precise velocity control and 3) high accuracy heading angle control. In addition to the conventional PID controller, model-based feedforward control, Model Following Control (MFC) for the anti-slip control of the wheel on the ice and Yaw Moment Observer (YMO) for the robust heading angle control are applied as key technologies for the STR driving. The design configurations of the STR to achieve the detection of its own location and throwing/curling of the stone is proposed in this paper as well as the detail of the precise driving control.

In this paper, Dynamic Dumbbell, a novel robotic device for advanced muscular exercise of upper limb is presented. The type of exercise load is classified and designed in terms of mechanical engineering to be implemented in Dynamic Dumbbell. The exercise load model, which is named as programmable exercise load, is realized by Dynamic Dumbbell. To generate the programmable exercise load, two of compact Planetary-geared Elastic Actuator, which is a rotary Series Elastic Actuator (SEA), are utilized in Dynamic Dumbbell. The SEAs are controlled using high performance force control algorithm. Experimental results verifies the effectiveness of the proposed Dynamic Dumbbell and programmable exercise load.

The tension control of wires can benefit from Series Elastic Actuator (SEA), which is a potential emerging actuator system. In this paper, it is verified that the tension of wires can be successfully controlled by a novel SEA, called Compact Planetary-geared Elastic Actuator (cPEA), which incorporates a planetary gear and a spring to achieve precise force sensing and compactness at the same time. The design of model-based tension control and impedance compensator using cPEA is introduced, and the experiments that show the effectiveness of the proposed control are provided.

In this paper, elastically actuated bi-articular manipulator is developed using a novel compact planetary geared elastic actuator. The newly developed SEA, which is compact and has little backlash, can achieve high force control performance. The configuration of the developed manipulator is designed based on the bi-articular muscle coordination, which can simplify the kinematics of the manipulator. The SEA and bi-articular actuator configuration of the developed manipulator can achieve high performance force control in the workspace, and thus can be utilized for various applications related to the service robot. The mechanism and control algorithm of the novel SEA, and the novel kinematics and dynamics of the developed manipulator are introduced in this paper. Impedance controller is designed based on the kinematics and dynamics of the manipulator and its performance is verified through experiments.

In this paper, novel mechanical mechanism and control method using SEA are suggested for natural gait pattern and effective gait rehabilitation. Conventional body weight support system (BWS) focuses on static position lifting and has limitation for a subject to constrain natural gait pattern especially in the vertical and medial-lateral movement. To overcome such abnormal gait pattern during BWS rehabilitation, modal force and torque control using wire is applied in this paper. The control makes it possible for a subject to generate natural gait motion which is natural in the vertical and medial-lateral movement during gait rehabilitation. To implement modal force and torque control, reference transformation for control of the tension of two wire is suggested. To control the tension of each wire, SEA which is controlled by the model base is utilized. And experiments are performed to assess the control performance.

Series Elastic Actuator(SEA) has been emerging as a novel and potential actuator system for many robotic applications. It is well known that SEA can achieve high compliance which realizes safe interaction between humans and robots. On the other hand, precision position control has been considered difficult in SEA applications. A novel control configuration for SEA position control is proposed in this paper to address this problem. Resonance Ratio Control (RRC) which has been applied for flexible system control is applied to an SEA, and it is compared with the conventional SEA position control strategy. In particular, the similarity of RRC and the force control of SEA is explained, and the control performances using two methodologies are compared.

This paper describes a wire-driven parallel robotic system for the maintenance of offshore wind turbines. This robotic system vertically climbs on towers or blades, and performs cleaning and inspection using waterjets and phased array ultrasonic testing (PAUT) devices, respectively. For a detailed mechanical design, mechanisms for (1) climbing towers or blades, (2) transition motion between towers and blades, (3) gripping blades, and (4) contact motion between PAUT devices and blade surfaces are proposed so that the robotic system can maneuver on towers and blades. For the motion analysis of the robotic system, nonholonomic constraints are analyzed and utilized in height and attitude control schemes, which are proposed to adapt varying nonholonomic constraints of blade surface and achieve the climbing motion on towers and blades. To validate these control schemes, we conduct experiment and analyze the performance of the proposed control schemes. The results show that the height and attitude control schemes for the robotic system do achieve the control goals and overcome the control challenges.

In many industrial fields, the mass information of a moving system is important and necessary to prevent undesired motion or failure and to control the system in its desired trajectory. One simple solution could be direct measurement of the mass using a sensor such as force sensor and accelerometer. However, it requires additional cost increase. In addition, it is not easy to measure the mass of a moving part in many cases. For those reasons, in this research, an online varying mass estimation algorithm is designed using an Extended Kalman Filter (EKF) without any additional sensors. Furthermore, the lumped disturbance compensating algorithm, which was designed by the authors in the previous research using EKF, is combined to obtain further position tracking performance. The effectiveness of the suggested method is validated through simulations. Additional verification with experiments is planned for future work.

Safety, compliance and human-friendliness are trending keywords in robotics now. The most significant reason for the growth in the use of these keywords is the progress of the service robot interacting with environments, including humans. Following these trends, Series Elastic Actuator (SEA) has received a large attention as a promising actuator in this field. Consequently, various SEA mechanisms have been developed by a lot of researchers ever since it was firstly introduced in 1990s. In spite of the development and applications at various SEAs, there still are challenging problems: backlash of gear reducer, encoder resolution problem, spring non-linearity, limited working range, etc. In this research, a novel SEA mechanism called compact Planetary geared Elastic Actuator (cPEA) is introduced at first. The proposed cPEA utilizes the planetary gear as a power transmission which has the compactness so that it can minimize the backlash in SEA motions. Series elasticity is achieved by the torsional spring which is placed in the redundant space of mechanism. Spring linearity, dynamics, sensitivity, mechanism of planetary gear as differential mechanism and force tracking performance with model-based controller are analyzed in this paper utilizing the proposed cPEA. From the results, the effectiveness of the proposed cPEA is verified.

Recently, the dynamic model of Series Elastic Actuator (SEA) has been researched intensively, and most of the approaches ignore the dynamics of the load part and model SEA as a simple mass damper spring system, which is valid only when SEAs contact with high impedance environments. To consider the dynamic model of SEA as a mass damper spring system can be erroneous when SEA does not contact high impedance environment and makes free motions. In this paper, a novel dynamic model of Reaction Force Series Elastic Actuator is proposed, which is unlumped two mass system model. The dynamic model is derived using the Lagrangian mechanics so as to successfully include all degrees of freedom of the SEA. The proposed model is verified through system identification experiments. The results indicate the actual dynamic model of SEA is valid throughout various load conditions.

This paper introduces a state estimation method for the position control of a two-DoF planar manipulator in the polar coordinate system. The kinematics and dynamics of the two-DoF manipulator are analyzed utilizing the biarticular actuation mechanism and the polar coordinate system, which makes it possible to express the equation of motion in an effective and convenient way. The dynamic equation with the proposed coordinate system and biarticular actuation mechanism is formalized into a state-space equation, and the state feedback controller is designed based on the derived state-space dynamics. As applications of the proposed method, a position tracking controller is designed at the end-effector. In addition, for implementation of the proposed method, a kinematic Kalman filtering is utilized for the best estimation of state variables.

A series elastic actuator (SEA) is a promising actuation method in robotics and mechatronics applications that intelligently interact with environments, including humans. The SEA is characterized by a spring placed between the load and an actuator, which is an electric motor in most SEA systems. Since the spring plays the role of a transducer between a position (i.e., spring deflection) and a force, it is able to control the output force (torque) precisely by utilizing typical position control methods. Also, realization of the precise force (torque) control implies that the SEA exhibits zero mechanical impedance, which renders its superior advantage in human-interactive systems. In many applications, however, the dynamic characteristics of an SEA have not been considered in controller design process, and mostly PID (Proportional-Integral-Derivative) control has been applied to as controllers for SEA. However, PID controller has various drawbacks including wind-ups and thus there are rooms to be improved for SEA control. This paper, taking into considerations this, proposes a dynamic model based control design of SEA. The dynamic characteristics of SEA are analyzed theoretically and experimentally, and feedback controllers based on the derived dynamics is proposed. Comparisons with conventional control methods verify the advantage of the proposed dynamic model based controller on control performance and force observation.

A number of control methodologies have been studied for assistive robotic technologies. Since the human motions in a daily life consist of multiple phases, such as walking, sitting and standing, controllers for assistive robots are required to be able to cope with different motion phases. For this reason, hybrid control which is able to occasionally switch control algorithms according to the motion phases has been preferred in the assistive robots, in particular wearable robots. In this paper, a generalized control framework is proposed as a fundamental framework for the hybrid assistive control and its stability is analyzed using the framework. The proposed control framework is implemented into a lower-limb exoskeleton robot and its effectiveness is verified thorough experiments.

In this paper, kinematics, statics, and dynamics of a two-link manipulator with a biarticular actuation mechanism are discussed. The biarticular actuation mechanism is inspired from the musculoskeletal structure of animals and is utilized in the controller design, as well as the mechanism design. For an effective and convenient expression of the equation of motion, the rotating coordinate system is adopted unlike the conventional robotic manipulators, the dynamics of which are obtained in the fixed coordinate system. It is proved in this paper that the biarticular actuation mechanism makes the control of the end-effector easier, more robust, and more intuitive than typical actuation mechanisms. Based on the derived equation of motion of a robotic manipulator in the rotating coordinate system, a disturbance-observer-based controller is proposed for realization of the Spring Loaded Inverted Pendulum (SLIP) model, which is a common model of human lower extremities but has seldom been realized in practice. The proposed methods are all verified by simulation studies in this paper.

Recently, offshore plants are demanded to secure natural resources more and more and it is strongly required unmanned ones for safety of human operators and less running costs. In this paper, a practical multi-user teleoperation system is proposed for monitoring, inspection, operation, and maintenance of the unmanned offshore plants. The proposed system is developed to control mobile manipulator in a cooperative way among multiple human operators for better performance. For this, two control schemes, hand-eye coordination and disjoint axes were introduced for easier intuitive control of the mobile manipulator and for better cooperative control among multi-user, respectively. A well-known passivity-based approach, the time-domain passivity approach was, in addition, adopted to maintain system stability. And then, the proposed multi-user teleoperation system was evaluated via a human-centered method with several quantitative metrics regarding task completion time and interaction forces. Experimental results showed that the proposed multi-user teleoperation system has the benefit in tasks requiring less task completion time and interaction forces.

This paper proposes a periodic adaptive disturbance observer (PADOB) for a precision position control of a PMLSM (Permanent Magnet Linear Synchronous Motor), which is based on a periodic adaptive learning control(PALC). It updates the output of a classical linear DOB to compensate modeling errors between a nominal plant and actual plant and external disturbance forces such as the friction and detent force. Therefore, it can improve problems occured by inaccurate parameters of the nominal plant and the instability problem occurred by updating parameters of nominal model in the DOB directly. Also, the complicated procedures to design the initial conditions in PALC are not needed. Through simulation test and experiments of the PMLSM, the validity of PADOB is illustrated.

There are many types of wheelchairs. Users are able to choose suitable wheelchair for their purposes. Power-assisted wheelchairs are one type of wheelchairs, which use both propelling torque from human and output torque from motors for their driving force. To improve assist performance, many assist control systems were proposed. One of conventional assist control, proposed by Seki et al., is designed for motion of traveling in straight line. However, it is difficult for wheelchair users to rotate using conventional assist control. In this paper, a novel two-dimensional assist control for power-assisted wheelchairs is proposed. The proposed assist control system is designed for both straight and rotational motion of wheelchair, therefore, power assist performance in rotating motion is improved compared to conventional system.

We have suggested a novel statics and force control can be achieved in a more simple way by using the biarticular muscle coordinate. In order to verify these characteristics, a robot arm with two links that are driven by planetary gear is developed in this paper. First, the complicated muscle structure is simplified as a three-pair six-muscle model including the biarticular muscle. Then based on the configuration, statics at the endeffector is redefined and a force control algorithm is suggested. The suggested statics and force control have the advantage of its simplicity. Then a novel robot arm to emulate the biarticular muscle is developed. A planetary gear system is adopted to transfer torque generated by a motor to two joints. Unnecessary coupling caused by the planetary gear is removed by disturbance observer control. Experiments done by the robot arm verifies the effectiveness of the suggested statics and force control.

Control design of self-servo track writer (SSTW) has become an important issue in hard disk drive research. This paper discusses the error propagation problem in SSTW control. Although the iterative learning control (ILC) has been suggested as a solution to suppress the error propagation in SSTW, existing suggestions design controllers in the iteration domain requiring considerable computation and complicated optimization algorithm. For this reason, this paper suggests SSTW control design in the time domain. First, reference correction to suppress the error propagation is suggested based on the error propagation study and a novel reference correction is suggested to control the amount of the converged error. Then, a state space approach is suggested developing a Kalman filter to estimate the absolute head position. The state space based design is extended and provides a formulation for a more general time-domain design of SSTW control.