In this paper, we propose a model predictive control (MPC) that accomplishes interactive robotic tasks, in which multiple contacts may occur at unknown locations. To address such scenarios, we made an explicit contact feedback loop in the MPC framework. An algorithm called Multi-Contact Particle Filter with Exploration Particle (MCP-EP) is employed to establish real-time feedback of multi-contact information. Then the interaction locations and forces are accommodated in the MPC framework via a spring contact model. Moreover, we achieved real-time control for a 7 degrees of freedom robot without any simplifying assumptions by employing a Differential-Dynamic-Programming algorithm. We achieved 6.8kHz, 1.9kHz, and 1.8kHz update rates of the MPC for 0, 1, and 2 contacts, respectively. This allows the robot to handle unexpected contacts in real time. Real-world experiments show the effectiveness of the proposed method in various scenarios.

This paper presents a model predictive control (MPC) method for redundant robots controlling multiple hierarchical tasks formulated as multi-layer constrained optimal control problems (OCPs). The proposed method, named hierarchical incremental MPC (HIMPC), is robust to dynamic uncertainties, untethered from kinematic/algorithmic singularities, and capable of handling input and state constraints such as joint torque and position limits. To this end, we first derive robust incremental systems that approximate uncertain system dynamics without computing complex nonlinear functions or identifying model parameters. Then the constrained OCPs are cast as quadratic programming problems which result in linear MPC, where dynamically-consistent task priority is achieved by deploying equality constraints and optimal control is attained under input and state constraints. Moreover, hierarchical feasibility and recursive feasibility are theoretically proven. Since the computational complexity of HIMPC drastically decreases compared with nonlinear MPC-based methods, it is implemented under the sampling frequency of 1 kHz for physical experiments with redundant manipulator setups, where robustness (high tracking accuracy and enhanced dynamic consistency), admissibility of multiple constraints, and singularity-avoidance nature are demonstrated and compared with state-of-the-art task-prioritized controllers.

Since modern robots are supposed to work closely together with humans, physical human-robot interaction is gaining importance. One crucial aspect for safe collaboration is a robust collision reaction strategy that is triggered after an unintentional physical contact. In this work, we propose a dynamically-consistent collision reaction controller, where the reactive motion is performed in one particular desired direction in Cartesian space, without disturbing the remaining ones. This results in more intuitive and more predictable behavior of the end-effector. In addition, the proposed reaction control law is independent of contact and internal observer dynamics used for collision detection. The theoretical claims are validated in simulation and experiments. The proposed reaction controller is experimentally compared with a conventional approach for collision reaction. All experiments have been conducted on a torque controlled KUKA LWR IV + lightweight robot.

Gait generation frameworks for humanoid robots typically assume a constant centroidal angular momentum (CAM) throughout the walking cycle, which induces undesirable contact torques in the feet and results in performance degradation. In this work, we present a novel algorithm to learn the CAM online and include the obtained knowledge within the closed-form solutions of the Divergent Component of Motion (DCM) locomotion framework. To ensure a reduction of the contact torques at the desired center of pressure position, a CAM trajectory is generated and explicitly tracked by a whole-body controller. Experiments with the humanoid robot TORO demonstrate that the proposed method significantly increases the maximum step length and walking speed during locomotion.

Reactivity to unforeseen disturbances is one of the most crucial characteristics for biped robots to walk robustly in the real world. Nevertheless, conventional walking methods generally have limited capability for generating rapid reactions to disturbances, because in these methods it is necessary to wait until the end of the preplanned time period to proceed to the next phase. In this study, to improve reactivity, we develop an event-based finite-state machine (E-FSM) for walking pattern generation. Reactivity is enhanced by determining the state transition conditions of the E-FSM only with time-independent events based on the present robot state. Moreover, in the E-FSM, the robot can walk robustly even when the center of mass and the swing foot motion are disturbed, by employing the capture point concept combined with a new swing foot position constraint. Finally, we propose to control the walking robot by incorporating the E-FSM with an inverse dynamics-based motion/force controller to achieve compliant behavior. This can provide safe responses to external disturbances. The developed method is verified by experiments on a 12-degrees-of-freedom torque-controlled biped robot while it locomotes under irregular external disturbances applied to the upper body or swing leg.

This paper proposes a novel and practical approach to enhance the computational efficiency of the hierarchical quadratic programming (HQP)-based whole-body control. The HQP method is known to offer control solutions satisfying strict priority with various constraints for multiple-tasks execution. However, it inherently comes at the price of high computation time to solve QP optimization problems in each hierarchical level which limits practicability in a real-time control system with fast sampling time. To mitigate this issue, we propose that the operational space formulation is incorporated into the HQP method, where the decision variables are intuitively defined at the task level and possess smaller dimensions. Indeed, it serves faster whole-body control solution for multiple tasks under equality and inequality constraints yet strictly fulfilling the task priority. The performance of the pro-posed method is experimentally verified on the actual floating-based humanoid, named TOCABI with 33 degrees-of-freedom. In addition, computation time is analyzed by comparison with conventional HQP and other advanced implementation forms.

High precision industrial applications call for equally precise functioning of industrial manipulators, which in turn requires accurate modeling of the manipulators. This paper carries out a detailed study on the modeling of industrial manipulators with elastic joints to improve their accuracy. In particular, the effect of adopting a simple harmonic drive (HD) model and ignoring a dynamic effect called low inertia coupling between the actuators and links on the model accuracy has been analyzed from a parameter estimation perspective. Since the aforementioned model characteristics have been generally ignored for high gear reduction ratios, this study is carried out with five different reduction ratios ranging from low to high, where three different models of a three-joints elastic manipulator are considered. The accuracy of the models is compared using the torque performance metrics of a predefined joint motion of the robot. Furthermore, the impact of the models with different accuracy is assessed by carrying out a state-of-the-art dynamic parameter estimation, and the resulting errors are compared to ascertain the merits of adopting a detailed elastic dynamic model of a manipulator.

Cable-driven joints proved to be an effective solution in a wide variety of applications ranging from medical to industrial fields where light structures, interaction with unstructured and constrained environments and precise motion are required. These requirements are achieved by moving the actuators from joints to the robot chassis. Despite these positive properties a cable-driven robotic arm requires a complex cable routing within the entire structure to transmit motion to all joints. The main effect of this routing is a friction phenomenon which reduces the accuracy of the motion of the robotic device. In this paper a bond-graph approach is presented to model a family of cable-driven joints including a novel friction model that can be easily implemented into a control algorithm to compensate the friction forces induced by the rope sliding into bushings.

This paper aims to develop a controller for a robot manipulator equipped with series elastic actuators (SEAs) to precisely track the desired link position coping with deflections from the intrinsic compliance. The well-known time-delay estimation (TDE) technique is modified for devising the new controller. In this paper, we first report that the conventional use of a constant gain matrix for the TDE framework is insufficient for high accuracy tracking because the tracking accuracy is significantly deteriorated and the closed-loop stability may be threatened. Accordingly, the new controller employs link inertia information with dynamic coupling terms to define the gain for TDE and then employs terminal sliding mode (TSM) control to enhance robustness and convergence speed. Particularly, the modified TDE is applied in the two-staged manner which enables to compensate the complicated nonlinear dynamics terms in SEA dynamics. The TSM synergistically amalgamates the accuracy, robustness, and convergence in tracking. The proposed controller is numerically validated by comparative experiments with a SEA-driven manipulator.

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 presents a dynamic whole-body control method for humanoids to render agile and stable standing-up motion based on energy concepts. First, to cope with the standing-up problem with multiple contacts in hierarchical tasks, an enhanced operational-space based whole-body control (WBC) framework is proposed, which offers optimal torque resolutions guaranteeing strict dynamic consistency with inequality constraints formulated by quadratic programming. Second, agile standing-up control strategy with dynamic push and rise actions is newly developed based on the notion of the total energy. The optimal pushing wrenches at contacts are computed to obtain sufficient energy to accelerate the center-of-mass (CoM) of the robot as quick as possible, and the total energy is then controlled to attain rapid rise-up motion and to stabilize the body of the robot. Consequently, the robot can effectively and actively stand up to recover from a certain pose in which cannot be accomplished by any quasi-static motion. The proposed method is numerically experimented and validated with dynamic parameters from the real humanoid COMAN+, fulfilling different types of standing-up actions.

This paper proposes a novel fall control technique based on energy concepts, which can be applied online to mitigate the impact forces incurred during the falling over of humanoids. The technique reduces the total energy using a nonlinear control tool, called energy shaping (ES), and further distributes the reduced energy over multiple contacts by means of energy distribution polygons (EDP). We also include an effective orientation control to safeguard the end-effectors in the event of ground impacts. The performance of the proposed method is numerically evaluated by dynamic simulations under the sudden falling over scenario of the humanoid robot for both lateral and sagittal falls. The effectiveness of the proposed ES and EDP concepts are verified by diverse comparative simulations with total energy, distribution, and impact forces.

The understanding of human arm stiffness have brought several significant advances to robotics. For the most part, the end-point stiffness of human arm serves as an important role in guiding and shaping the Cartesian stiffness of robot arm in the execution of complicated interaction tasks because of the convenience of using the common space where both stiffnesses function. However, investigation of the joint stiffness of human arm, on the other hand, will provide a more comprehensive perspective on the human arm stiffness and enable other appealing robotic applications, for instance, whole-arm interaction with unstructured environment. As a fundamental research for these applications, the feasibility of an online joint stiffness transfer approach from human to anthropomorphic arms is discussed in this paper. This is realized by a proposed concept of physiological joint stiffness, which is shared by the human and anthropomorphic arms. The desired joint stiffness of robot arm is transformed from the estimated joint stiffness of human arm by requiring both arms to have the same apparent physiological joint stiffness. To make the calculated joint stiffness achievable in a robot controller, the stiffness matrix is subsequently optimized to be symmetric and positive definite. Proof-of-concept experiment is performed on a fully integrated robotic teleoperation setup to validate the efficacy of the proposed method.

In this paper, the well-known problem of codependence between inverse dynamics torque and contact force in bimanual object manipulation is addressed. The common contact constraint, namely rigid grasping, is exploited to decompose the set of dynamics equations into two orthogonally decoupled sets. Subsequently, the inverse dynamics control is formulated in a sub-manifold that is independent of the contact force, leading to analytically correct solutions that do not need to resort to common approximations for the aforementioned codependence problem. The contact force is also analytically computed and, therefore, can be optimally distributed using the torque redundancy. Relying on this prediction is most significant in situations where a force sensor at the end-effector is not present or is faulty. Even in the availability of sensory data, the predicted force may be used to correct typically noisy or delayed when filtered measurements, resulting in improved robustness. Simulation experiments on a planar bimanual manipulation model are presented.

This paper focuses on the development of a dynamic model-free whole-body controller for a humanoid robot with high kinematic redundancy. The proposed controller is based on force-level operational-space control framework, which computes joint torques for the required forces of prioritized multiple tasks. While typical approaches based on this framework require to obtain an accurate robot dynamics model, which has been generally recognized as a major hurdle to overcome for implementation in real humanoid robots, the proposed controller incorporates adaptive sliding-mode and online dynamics estimation schemes; thus, it can be easily realized on a humanoid without identifying complex robot dynamic parameters. As a result, the gains of the proposed controller are adaptively adjusted to assure the control accuracy, when the humanoid robot changes its posture and undergoes uncertain disturbances. Experiments with a 23-DoFs humanoid under uncertain disturbances verify that the proposed controller can robustly perform multiple tasks with high accuracy.

A common disadvantage of multi-legged robots is that they often lack the manipulation capability. To overcome this limitation, an arm can be added to the body of the multi-legged robot, to perform manipulation tasks and provide assistance for locomotion. First, we proposed an attachment configuration of the arm for a multi-legged robot that provide a uniform workspace in front, below and above the base robot trunk. Second, an integrated control framework promises to keep the mobility and the balance of the mobile platform and provides precise manipulation capability of the arm incorporating a payload estimation scheme. Finally, we verify an integrated control framework with experimental results of a static and walking mobile platform while moving the arm.

It is well known that kinematics can significantly affect the manipulation capabilities of robotic arms, traditionally illustrated by performance indices such as workspace volume, kinematic and force manipulability, and isotropy within the arm workspace. In the case of dual-arm systems and bimanual manipulation tasks, the kinematics effects to the above indices becomes even more apparent. However, in spite of the large number of dual-arm systems developed in the past, there is a little literature on the kinematic design analysis for the development of such systems. Particularly, the effects of configuration/ orientation of the shoulders' placement with respect to the torso structure have not sufficiently studied or considered, while many dual-arm systems with upward and/or forward tilt angle in shoulder base frame have been introduced. This paper addresses this problem and quantifies the effect of shoulders base frame orientation in a dual-arm manipulation system by looking at its effect on several important manipulation indices, such as the overall and common workspace, redundancy, global isotropy, dual-arm manipulability, and inertia ellipsoid index within the common workspace of the two arms. Consequently, a range of upward and forward tilt angles for the shoulder frames is identified for the design of a dual-arm torso system to render the most desired manipulation performance.

This paper proposes an optimization method for dual-arm robots, inspired by a study on human asymmetric bimanual action called Guiard's principle which states that when humans perform asymmetric bimanual tasks, the right hand (as the lateral preference) performs a fine motion (and force) resolution, while the left hand performs a coarse resolution. To effectively transfer the human bimanual-task knowledge to dual-arm robots, we proposed a cost function, based on task-compatibility index, which is used to set the desired motion and force resolution for each end-effector of the dual-arm according to its role in the bimanual action. Thus the right-arm posture is optimized such that the tool attached to its end-effector can exert fine motion and force. And the left-arm posture is optimized to assume a strong and dynamic structural support for the right arm action. We experimentally compare the proposed cost function against previous methods for dual-arm robots using two six degrees-of-freedom torque-controlled manipulators. The control performance, when mimicking Guiard's principle shows considerably better results.

Incorporation of human motor control principles in the motion control architectures for humanoid robots or assistive and prosthesis devices will permit these systems not only to look anthropomorphic and natural at the body ware level but also to generate natural motion profiles resembling those executed by humans during manipulation and locomotion. In this work, relying on the observations on human bimanual coordination, a novel realtime motion control strategy is proposed to regulate the desired Cartesian stiffness profile during the execution of bimanual tasks. The novelty of the proposed control scheme relies on the use of common mode stiffness (CMS) and configuration dependent stiffness (CDS) to regulate the size and directionality of the task space stiffness ellipsoid. Thanks to the CDS control, the proposed scheme is not only proved to be effective in regulating the desired stiffness ellipsoid but also permits to resolve the manipulator redundancy in a natural manner. The effectiveness of the controller is evaluated in an experimental setup in which two cooperating robotic arms are executing an assembly task. Experimental results demonstrate that the proposed dual-arm CDS-CMS controller is effective in tracking the desired stiffness ellipsoids as well as in producing human-like natural motions for the two robotic arms.

Recently-developed variable damping mechanisms have been exploited as a complement to compliant actuators. While accurate knowledge and control of generated damping is essential for achieving the desired performance, no physical sensor measuring the damping exists. This work introduces a novel non-model-based approach for the estimation of time-variant damping for variable impedance actuation systems. The approach is based only on torque and position/velocity measurements; without the knowledge of system's inputs, to ensure the estimation of both intentional and unintentional changes. Hence, a recursive least square estimator, modified for achieving a proper convergence for the estimation of time-variant parameters, is exploited. Experiments on a variable physical damping actuator are also presented to validate the performance of proposed approach.

On a new demand of safe human-robot interaction for robotic applications, the Compact Compliant Actuator, named CompActTM, is recently developed with physical compliance and active variable damping. In this mechanism, a desired physical damping behavior is realized by generating a friction force which is actively controlled by piezoelectric actuators (PEAs). However, nonlinearities such as hysteresis and creep effect make difficult to precisely control the generated piezoelectric force. This paper focuses on a development of precise force tracking controller for PEAs. A time delay estimation (TDE) using a force feedback is newly proposed to compensate a hysteretic behavior of the PEA and external uncertainties without a mathematical model. Thanks to the force-based TDE, the proposed control is accurate, computationally efficient and easily implementable on the real PEA system. The proposed control scheme is experimentally verified on the CompActTM. Root-mean-square values of the steady-state error for step commands are kept as less than error ratio of 0.13 % and the closed-loop system bandwidth for sinusoidal commands of 20 N stroke is confirmed as about 11 Hz under 100 N payload. In addition, the stability of the proposed control is proved to be bounded-input-bounded-output (BIBO) stable.

The need for safe human-robot interaction in emerging robotic applications has recently driven the development of new range of actuation systems spanning from variable stiffness drives to variable damping or full variable impedance joints. Concerning the provision of variable physical damping in compliant actuators, the main objective is to improve the control of compliant joint. In a particular class of these variable physical damping actuators (VPDAs), the level of generated damping is realized by creating a friction force which is actively controlled by piezoelectric actuators (PEAs). Therefore, to effectively control the damping output, the accurate force control of the PEAs is required. However, difficulties to precisely control the generated piezoelectric force stem from its highly nonlinear behavior such as hysteresis and creep effect. This paper presents a novel practical force tracking controller for PEAs with unknown hysteresis behavior. The proposed control consists of two elements: terminal sliding-mode based desired dynamics injection and model-free compensation for nonlinear dynamics of PEAs, which allow fast convergence and extraordinary robustness to the closed-loop system. The stability of the overall system is proved in the sense of Lyapunov. On the real prototype of VPDA, the proposed control scheme is experimentally verified and analyzed by comparison to other controllers, demonstrating improved force tracking performance of PEAs in VPDA system.

This paper presents new formulations in task-prioritization for dual-arms with multiple, conflicting tasks and experimental validations. An essential part of the proposed method is the use of relative Jacobian that treats the dual-arm as an equivalent single arm. As a result, three formulations are derived. The first formulation, called relative task prioritization, expresses a task prioritization at the acceleration level for a dual-arm, with multiple tasks, that is controlled as a single manipulator. The second formulation is an impedance control equation that allows direct control of the relative motion and impedance between two end-effectors. Our third formulation is a control law that combines relative task prioritization, impedance control, and time-delay estimation, which contributes to the ease of implementation of our proposed method. In the physical implementation, one arm draws a circle on a plate attached to the other arm in parallel with three subtasks. Then, intentional conflict among subtasks is induced. The experimental results show that when such conflict occurs, the higher priority task is guaranteed an immediate execution without influence from the lower priority task.

This paper proposes a control strategy for a compliant actuator, the CompAct™ actuator, which is equipped with semi active friction dampers in its transmission system. Both the transmission flexibility and the nonlinearity of the friction based damping torque makes the control of this actuator not a trivial task. This paper studies model of the presented actuator and the control problem of accurate link position tracking based on sliding mode approach that considers the friction torque as an uncertainty. Stability analysis and simulations highlight the effectiveness of the proposed controller in compensating for the deflections and unknown friction torque of the actuator. The performance of the controller is also validated by experiment results that demonstrate the tracking performance of the CompAct™ actuator achieved by the presented control strategy.

This paper focuses on a kinematic redundancy resolution of bimanual robotic system for a machining task as a part of factory automation. Inspired by a study of human bimanual action, called Guiard's principles, a cost function is proposed by using task-compatibility indices. An acceleration-level redundancy resolution is provided via optimization of the cost function in order to reflect the role of human arm movement: one arm performs coarse motion, and the other fine motion. A dynamic simulation with two 6 degrees-of-freedom robots shows the effectiveness of the proposed idea.

In this paper, the practical problems of the Operational Space Formulation (OSF) are considered. The OSF provides decentralized control of the tasks by virtue of the ‘dynamic decoupling property’. In the practical view point, however, the OSF can be unfavorable due to the inevitable modeling error and large computational effort. As a remedy for this problem, the OSF is enhanced with Time-Delay Estimation (TDE) scheme. The robustness and efficiency of the proposed control have been analyzed and demonstrated to be effective against the practical problems while preserving the dynamic decoupling property.