Adaptive Compliance Control Research Articles

Trajectory Deformation-Based Multi-Modal Adaptive Compliance Control for a Wearable Lower Limb Rehabilitation Robot.

Adaptive compliance control is critical for rehabilitation robots to cope with the varying rehabilitation needs and enhance training safety. This article presents a trajectory deformation-based multi-modal adaptive compliance control strategy (TD-MACCS) for a wearable lower limb rehabilitation robot (WLLRR), which includes a high-level trajectory planner and a low-level position controller. Dynamic motion primitives (DMPs) and a trajectory deformation algorithm (TDA) are integrated into the high-level trajectory planner, generating multi-joint synchronized desired trajectories through physical human-robot interaction (pHRI). In particular, the amplitude modulation factor of DMPs and the deformation factor of TDA are adapted by a multi-modal adaptive regulator, achieving smooth switching of human-dominant mode, robot-dominant mode, and soft-stop mode. Besides, a linear active disturbance rejection controller is designed as the low-level position controller. Four healthy participants and two stroke survivors are recruited to conduct robot-assisted walking experiments using the TD-MACCS. The results show that the TD-MACCS can smoothly switch three control modes while guaranteeing trajectory tracking accuracy. Moreover, we find that appropriately increasing the upper bound of the deformation factor can enhance the average walking speed (AWS) and root mean square of trajectory deviation (RMSTD).

A Compliant Force Control Scheme for Industrial Robot Interactive Operation

To meet the enormous demand for smart manufacturing, industrial robots are playing an increasingly important role. For industrial operations such as grinding 3C products, numerous demands are placed on the compliant interaction ability of industrial robots to interact in a compliant manner. In this article, an adaptive compliant control framework for robot interaction is proposed. The reference trajectory is obtained by single-point demonstration and DMP generalization. The adaptive feedforward and impedance force controller is derived in terms of position errors, and they are input into an admittance controller to obtain the updated amount of position deviation. The compliant interaction effect is achieved, which is shown that the grinding head fits on the curved surface of a computer mouse, and the interaction force is within a certain expected range in the grinding experiment based on the performance an Elite robot. A comparative experiment was conducted to demonstrate the effectiveness of the proposed framework in a more intuitive way.

Development of an autonomous robotic system for beard shaving assistance of disabled people based on an adaptive force tracking impedance control

Recently, people with upper arm disabilities due to neurological disorders, stroke or old age are receiving robotic assistance to perform several activities such as shaving, eating, brushing and drinking. Although the full potential of robotic assistance lies in the use of fully autonomous robotic systems, these systems are limited in design due to the complexities and the associated risks. Hence, rather than the shared controlled or active robotic systems used for such tasks around the head, an adaptive compliance control scheme-based autonomous robotic system for beard shaving assistance is proposed. The system includes an autonomous online face detection and tracking as well as selected geometrical features-based beard region estimation using the Kinect RGB-D camera. Online trajectory planning for achieving the shaving task is enabled; with the capability of online re-planning trajectories in case of unintended head pose movement and occlusion. Based on the dynamics of the UR-10 6-DOF manipulator using ADAMS and MATLAB, an adaptive force tracking impedance controller whose parameters are tuned using Genetic Algorithm (GA) with force/torque constraints is developed. This controller can regulate the contact force under head pose changing and varying shaving region stiffness by adjusting the target stiffness of the controller. Simulation results demonstrate the system capability to achieve beard shaving autonomously with varying environmental parameters that can be extended for achieving other tasks around the head such as feeding, drinking and brushing.

Parameter identification and adaptive compliant control of rehabilitation exoskeleton based on multiple sensors

• We establish a coupling kinematics/dynamics model by human-machine coupling relationship. • We address an estimation method of active joint torque of human lower limbs. • A reference trajectory adaptive compliance control algorithm is proposed. To help rehabilitation of patients with lower limb dysfunction, a sitting/lying exoskeleton robot is designed for lower limb rehabilitation. Firstly, a coupling kinematics/dynamics model, including the wearer and exoskeleton, is established by the in-depth analysis of human-machine coupling relationship, and the prototype structure is introduced. Furthermore, according to the kinetic parameter identification method, an estimation method of active joint torque of human lower limbs is proposed to realize the prediction of human motion intention, which is the basis of the reference motion trajectory. Moreover, a reference trajectory adaptive compliance control algorithm is proposed. Finally, the human-computer interaction force is measured by the torque sensor, the effectiveness of the parameter identification and compliance control algorithm is verified.

Reinforcement learning based compliance control of a robotic walk assist device

ABSTRACTMillions of people around the globe have to deal with walking disability. Robotic walk assist devices can help people with walking disabilities, especially those with weak legs. However, safety, cost, efficiency and user friendliness are some of the key challenges. For robotic walk assist devices, light weight structure and energy efficient design as well as optimal control are vitally important. In addition, compliance control can help to improve the safety of such devices as well as contribute to their user friendliness. In this paper, an optimal adaptive compliance control is proposed for a Robotic walk assist device. The suggested scheme is based on bio-inspired reinforcement learning. It is completely dynamic-model-free scheme and employs joint position and velocity feedback as well as sensed joint torque (applied by user during walk) for compliance control. The efficiency of the controller is tested in simulation on a robotic walk assisting device model.

Exoskeleton design and adaptive compliance control for hand rehabilitation

An adaptive robotic system has been developed to be used for hand rehabilitation. Previously developed exoskeletons are either very complex in terms of mechanism, hardware and software, or simple but have limited functionality only for a specific rehabilitation task. Some of these studies use simple position controllers considering only to improve the trajectory tracking performance of the exoskeleton which is inadequate in terms of safety and health of the patient. Some of them focus only on either passive or active rehabilitation, but not both together. Some others use EMG signals to assist the patient, but this time active rehabilitation is impossible unless different designs and control strategies are not developed. The proposed mechanical structure is extremely simple. The middle and the proximal phalanxes are used as a link of consecutively connected two 4-bar mechanisms, respectively. The PIP and MCP joints are actuated by a single electro mechanical cylinder to produce complex flexion and extension movements. It is simpler than similar ones from aspect with the mechanical structure and the biodynamic fit of the hand, making it practicable in terms of production and personal usage. Simple design lets to implement adaptive compliance controller for all active and passive rehabilitation tasks, instead of developing complex and different strategies for different rehabilitation tasks. Furthermore, using the Luenberger observer for unmeasured velocity state variable, an on-line estimation method is used to estimate the dynamic parameters of the system. This makes possible to estimate the force exerted by the patient as well, without a force sensor.

A Multistate Friction Model for the Compensation of the Asymmetric Hysteresis in the Mechanical Response of Pneumatic Artificial Muscles

These days, biomimetic and compliant actuators have been made available to the main applications of rehabilitation and assistive robotics. In this context, the interaction control of soft robots, mechatronic surgical instruments and robotic prostheses can be improved through the adoption of pneumatic artificial muscles (PAMs), a class of compliant actuators that exhibit some similarities with the structure and function of biological muscles. Together with the advantage of implementing adaptive compliance control laws, the nonlinear and hysteretic force/length characteristics of PAMs pose some challenges in the design and implementation of tracking control strategies. This paper presents a parsimonious and accurate model of the asymmetric hysteresis observed in the force response of PAMs. The model has been validated through the experimental identification of the mechanical response of a small-sized PAM where the asymmetric effects of hysteresis are more evident. Both the experimental results and a comparison with other dynamic friction models show that the proposed model could be useful to implement efficient compensation strategies for the tracking control of soft robots.

Hierarchical Compliance Control of a Soft Ankle Rehabilitation Robot Actuated by Pneumatic Muscles.

Traditional compliance control of a rehabilitation robot is implemented in task space by using impedance or admittance control algorithms. The soft robot actuated by pneumatic muscle actuators (PMAs) is becoming prominent for patients as it enables the compliance being adjusted in each active link, which, however, has not been reported in the literature. This paper proposes a new compliance control method of a soft ankle rehabilitation robot that is driven by four PMAs configured in parallel to enable three degrees of freedom movement of the ankle joint. A new hierarchical compliance control structure, including a low-level compliance adjustment controller in joint space and a high-level admittance controller in task space, is designed. An adaptive compliance control paradigm is further developed by taking into account patient’s active contribution and movement ability during a previous period of time, in order to provide robot assistance only when it is necessarily required. Experiments on healthy and impaired human subjects were conducted to verify the adaptive hierarchical compliance control scheme. The results show that the robot hierarchical compliance can be online adjusted according to the participant’s assessment. The robot reduces its assistance output when participants contribute more and vice versa, thus providing a potentially feasible solution to the patient-in-loop cooperative training strategy.

A Nonlinear Adaptive Compliance Controller for Rehabilitation

A Nonlinear Adaptive Compliance Controller for Rehabilitation

Compliance Control and Human–Robot Interaction: Part II — Experimental Examples

Compliance control is highly relevant to human safety in human–robot interaction (HRI). This paper presents multi-dimensional compliance control of a humanoid robot arm. A dynamic model-free adaptive controller with an anti-windup compensator is implemented on four degrees of freedom (DOF) of a humanoid robot arm. The paper is aimed to compliment the associated review paper on compliance control. This is a model reference adaptive compliance scheme which employs end-effector forces (measured via joint torque sensors) as a feedback. The robot's body-own torques are separated from external torques via a simple but effective algorithm. In addition, an experiment of physical human robot interaction is conducted employing the above mentioned adaptive compliance control along with a speech interface. The experiment is focused on passing an object (a cup) between a human and a robot. Compliance is providing an immediate layer of safety for this HRI scenario by avoiding pushing, pulling or clamping and minimizing the effect of collisions with the environment.

Adaptive on-line parameter identification of a steer-by-wire system

Adaptive compliance control strategy can be a significant advantage for control of steer-by-wire systems. Initially the method is proposed for robotic applications where the main concern is the interaction forces between the robot and its environment. There are several studies about cooperative working of a robot and a human. As long as the steering system is a part of the vehicle where driver interaction is involved, it is reasonable to think that compliance control strategies can be adapted to steer-by-wire systems. Compliance control is a model reference control (MRC) strategy where the measured external force/torque is used as an input to a reference model to calculate its output and where the real system is controlled appropriately to track the reference system output. If a sensor is available to measure the external force/torque, system parameters need not to be estimated. A constant gain feedback controller can be used in such a case. However, if the parameter variations of the system are not within certain bounds, a model reference adaptive controller (MRAC) is needed. In addition to this, examining the change in the dynamics of the system due to the compliance of the driver arms is not possible by direct MRAC, because the driver effect is considered as a disturbance in this strategy. Therefore, in this study, instead of estimating controller parameters using direct MRAC where the main concern is the tracking performance, it is considered to use indirect MRAC in which the system parameters are estimated to observe their variations in the presence of parametric uncertainty and disturbances and to further examine the change in the dynamics of the system due to the compliance of the driver arms forming a closed kinematic structure by constraining the steering wheel. Hence, a steer-by-wire experimental setup including driver interaction and vehicle directional control units has been developed and three well-known adaptive on-line estimation methods, which are output-error method, equation-error method and modified recursive least squares method are evaluated on the driver interaction unit. These three methods are compared in terms of computational complexity, convergence, stability and applicability to real vehicles.

Adaptive compliance control of a hydraulic manipulator in free forging

The increased demand for large size forgings has led to developments and innovations of heavy-duty forging manipulators. Besides the huge carrying capacity, forging manipulators should possess robot features, such as force perception, delicacy, and flexibility. The aim of this work is to develop a practical compliance control method for hydraulic forging manipulators. A hybrid force–position control method is proposed and performed on a novel serial–parallel forging manipulator designed by the author’s institute. A specific study is carried on a hybrid pressure–position control system. The simulated and experimental results show the control method is feasible. The experiment on hybrid control is executed on a programmable logic controller considering industrial applications.

Safe Adaptive Compliance Control of a Humanoid Robotic Arm with Anti-Windup Compensation and Posture Control

Safety is very important for physical human-robot interaction. Compliance control can solve an important aspect of the safety problem by dealing with impact and other forces arising during close contact between humans and robots.

Adaptive compliance control of a multi‐legged stair‐climbing robot based on proprioceptive data

PurposeThe purpose of this paper is to describe an innovative compliance control architecture for hybrid multi‐legged robots. The approach was verified on the hybrid legged‐wheeled robot ASGUARD, which was inspired by quadruped animals. The adaptive compliance controller allows the system to cope with a variety of stairs, very rough terrain, and is also able to move with high velocity on flat ground without changing the control parameters.Design/methodology/approachThe paper shows how this adaptivity results in a versatile controller for hybrid legged‐wheeled robots. For the locomotion control we use an adaptive model of motion pattern generators. The control approach takes into account the proprioceptive information of the torques, which are applied on the legs. The controller itself is embedded on a FPGA‐based, custom designed motor control board. An additional proprioceptive inclination feedback is used to make the same controller more robust in terms of stair‐climbing capabilities.FindingsThe robot is well suited for disaster mitigation as well as for urban search and rescue missions, where it is often necessary to place sensors or cameras into dangerous or inaccessible areas to get a better situation awareness for the rescue personnel, before they enter a possibly dangerous area. A rugged, waterproof and dust‐proof corpus and the ability to swim are additional features of the robot.Originality/valueContrary to existing approaches, a pre‐defined walking pattern for stair‐climbing was not used, but an adaptive approach based only on internal sensor information. In contrast to many other walking pattern based robots, the direct proprioceptive feedback was used in order to modify the internal control loop, thus adapting the compliance of each leg on‐line.

<i>L</i><sub>2</sub>外乱減衰性能を考慮したマニピュレータの適応コンプライアンス制御

<i>L</i><sub>2</sub>外乱減衰性能を考慮したマニピュレータの適応コンプライアンス制御

Nonlinear and Adaptive Control of Force and Compliance in Manipulators

This paper presents new position-based force and compliance con trol schemes for robot manipulators using nonlinear and adaptive controllers. The proposed controllers are simple and can easily be implemented in the outer feedback loop that encloses the inner Cartesian position control system supplied by the robot manufac turer. In the position-based force control approach, adaptive PID and nonlinear PI controllers are proposed for setpoint tracking in which the controller gains are adjusted on-line as functions of the force error. In the position-based compliance control approach, nonlinear and adaptive PD controllers are developed to achieve a desired behavior at contact, where the controller gains are func tions of the contact force. Dynamic simulation results for a 7-DOF Robotics Research Corporation (RRC) arm are presented to demon strate the efficacy of the adaptive compliance control scheme in executing contact tasks. Experimental results are also presented to illustrate nonlinear force control of the RRC arm. The results demonstrate that the proposed nonlinear PI controller, where the integral gain is a sigmoidal function of the force error, yields supe rior performance compared to afixed-gain PI controller by produc ing a fast force response with a small settling time while preventing oscillations. Finally, the nonlinear PD compliance controller is im plemented on the RRC arm and experimental results are presented. These results demonstrate that the nonlinear PD controller, where the proportional gain is a hyperbolic function of the contact force, exhibits less sensitivity to the surface stiffness than afixed-gain PD controller.

Adaptive compliant control of robot manipulators

An adaptive compliant control for robot manipulators is presented in this paper. The control law is designed in the task space and contains a nonlinear model-based term and a linear compensator action. This is obtained as a combination of the position error, the velocity error and the integral of the force error. The scheme is made adaptive with respect to the dynamic parameters of the model of the robot manipulator. By using the classical Lyapunov method, it is demonstrated that the proposed control law ensures tracking of the unconstrained components of the desired end-effector trajectory, with regulation of the desired contact force along the constrained direction. Experiments are developed for an industrial robot manipulator in contact with an elastic surface.

Decentralized adaptive compliance control of robot manipulators

SummaryThis paper presents two adaptive schemes for controlling the end-effector compliance of robot manipulators. Each controller possesses a decentralized structure, in which the control input for each configuration degree-offreedom (DOF) is computed based on information concerning only that DOF. The first scheme is developed using an adaptive impedance control approach and consists of two subsystems: a simple “filter” which modifies the end-effector position trajectory based on the sensed contact force and the desired dynamic relationship between the position and force, and an adaptive controller that produces the joint torques required to track this modified trajectory. The second compliant motion control strategy is an adaptive admittance controller for position-controlled manipulators. In this scheme a desired contact force is specified and then position setpoints for the “inner-loop” position controller are generated which ensure that this desired force is achieved. The proposed controllers are extremely simple computationally, do not require knowledge of the manipulator dynamic model or parameter values of the manipulator or the environment, and are implemented in decentralized form.

Decentralized adaptive compliance control of robot manipulators

This paper presents two decentralized adaptive schemes for controlling the end-effector compliance of robot manipulators. The first scheme is developed using an adaptive impedance control approach for torque-controlled manipulators, while the second strategy is an adaptive admittance controller for position-controlled manipulators. The proposed controllers are very general and computationally efficient since they do not require knowledge of the manipulator dynamic model or parameter values of the manipulator or the environment. It is shown that the control strategies are globally stable in the presence of bounded disturbances, and that in the absence of disturbances the ultimate bound on the size of the system errors can be made arbitrarily small. The capabilities of the proposed control schemes are illustrated though laboratory experiments with a Robotics Research Corporation seven degree-of-freedom (DOF) manipulator.

Adaptive compliant control for an inspection robot system

A robotic sub-sea inspection system is described. Emphasis is placed on how to use self-tuning adaptive control strategies to control the robot compliant motion. Experiments on a PUMA robotic manipulator have shown that adaptive control can greatly improve contact quality and provide much better tracking ability in an unknown environment. Also adaptive controllers can make the approach time shorter than ordinary fixed gain controllers. A coupled dynamics concept for surface contact, which is typical in an inspection task, is introduced. Implementation of an adaptive controller in VAL-2 is detailed. A supervisory control system, capable of incorporating real-time compliant motion control and written in MODULA-2, is also described.