Environmental Adaptive Control of a Snake-like Robot With Variable Stiffness Actuators

This work investigates adaptive stiffness control and motion optimization of a snake-like robot with variable stiffness actuators. The robot can vary its stiffness by controlling magnetorheological fluid(MRF) around actuators. In order to improve the robot's physical stability in complex environments, this work proposes an adaptive stiffness control strategy. This strategy is also useful for the robot to avoid disturbing caused by emergency situations such as collisions. In addition, to obtain optimal stiffness and reduce energy consumption, both torques of actuators and stiffness of the MRF braker are considered and optimized by using an evolutionary optimization algorithm. Simulations and experiments are conducted to verify the proposed adaptive stiffness control and optimization methods for a variable stiffness snake-like robots.     

Adaptive impedance control of a variable stiffness actuator

This paper proposes an optimal impedance control method for a variable stiffness actuator (VSA), in which a variable stiffness mechanism and an actuator are aligned in series. First, we introduce a circuit expression of the robotic system and provide a unified framework to determine an optimal index of robots driven by VSAs, irrespective of the presence or absence of the environment. Next, we design a torque controller for a one-degree-of-freedom (DOF) robot and find the optimal condition of the stiffness in the VSA for a given task. Then, we design a stiffness control law for the VSA exploiting the intrinsic indivisible property between motion and passive impedance. This stiffness control law adaptively tunes the passive stiffness to minimize the energy consumption without defining any explicit desired impedance, which is usually required in impedance controllers. The stability of the closed loop system is proved using Lyapunov’s analysis. Simulations and experimental results validate the effectiveness of the proposed method and the robustness in response to parameter changes.     

Variable stiffness control for SEAs in rehabilitation training

ABSTRACT

Series Elastic Actuator (SEA) with both security and high performance is used extensively for rehabilitation robots with physical interaction. Human joints applied for motion therapy show variable stiffness properties during the process of rehabilitation training. When using robot to do motion therapy, impedance control is one of the most popular methods for rehabilitation works. However, impedance control with constant stiffness usually produces rigidity in the body due to natural changes of muscle tension. It may seriously restrict the achievement of excellent training effect and may even cause harm to patients. In this study, a novel real-time parallel variable stiffness control method is proposed based on cascade impedance controller. First, an SEA joint is analyzed and the limit factor of the impedance frequency is discussed. Subsequently, cascade impedance controller scheme with stiffness adjustment regulator is utilized to achieve the stiffness and the passivity of the controller is proved. Based on the scheme, a novel stiffness self-adjustment algorithm is presented which can regulate the stiffness by impedance approximation. Finally, simulation and experimental results are provided to validate the stiffness adjustment method during the rehabilitation process.     

Hierarchical control of end-point impedance and joint impedance forredundant manipulators

This paper proposes an impedance control method for redundant manipulators, which can control not only the end-point impedance using one of the conventional impedance control methods, but the joint impedance which has no effects on the end-point impedance. First, a sufficient condition for the joint impedance controller is derived. Then, the optimal controller for a given desired joint impedance is designed using the least squares method. Finally, computer simulations and experiments using a planar direct-drive robot are performed in order to confirm the validity of the proposed method     

A robot test-bed for assistance and assessment in physical therapy

This paper describes an experimental test-bed that was developed to assist and assess rehabilitation during physical and occupational therapy. A PUMA 260 robot was used with a controller and interface software developed in-house. The robot is designed to operate in two modes: (1) passive and (2) active. In the passive mode, the robot moves the subject's arm through specified paths. In the active mode, a subject guides the robot along a predefined path overcoming specified joint stiffness. In this mode, the controller compensates for gravity so that the robot can support its own weight in an arbitrary configuration. The developed graphical interface enables display of the current configuration of the robot in real-time, and allows us to customize experiments for a subject, and collect force and position data during an experiment. The results of a preliminary study with healthy subjects using this test-bed are also presented along with issues involved in the choice of paths and interpretation of the results.     

Model reference adaptive impedance control in Cartesian coordinates for physical human–robot interaction

In this paper, a nonlinear model reference adaptive impedance controller is proposed and tested. The controller provides asymptotic tracking of a reference impedance model for the robot end-effector in Cartesian coordinates applicable to rehabilitation robotics or any other human–robot interactions such as haptic systems. The controller uses the parameters of a desired stable reference model which is the target impedance for the robot’s end-effector. It also considers uncertainties in the model parameters of the robot. The asymptotic tracking is proven using Lyapunov stability theorem. Moreover, the adaptation law is proposed in joint space for reducing the complexity of its calculations; however, the controller and the stability proof are all presented in Cartesian coordinates. Using simulations and experiments on a two DOFs robot, the effectiveness of the proposed controller is investigated.     

Improving feasibility of robotic milling through robot placement optimisation

Milling performed with robots is quite demanding, even for low-strength materials, due to the high accuracy requirements, the generally high and periodically varying milling forces and the low stiffness of robots compared to CNC machine tools. In view of the generally improved recently robot stiffness, it is desirable to perform the milling operation in regions of the robot’s workspace where manipulability, both kinematic and dynamic, is highest, thereby exhausting the robot’s potential to cope with the process. In addition, by selecting the most suitable initial pose of the robot with respect to the workpiece, a reduction in the range of necessary joint torques may be reached, to the extent of alleviating the heavy requirements on the robot. Two genetic algorithms (GAs) are employed to tackle these problems. The values of several robot variables, such as joint positions and torques, which are needed by the genetic algorithms, are calculated using inverse kinematics and inverse dynamics models. In addition, initial positions and poses leading to singularities along the milling path are penalized and, thus, avoided. The first GA deals solely with robot kinematics to maximize manipulability. The second GA takes into account milling forces, which are computed numerically according to the particular milling parameters, to minimise joint torque loads.     

A real-time impedance-based singularity and joint-limits avoidance approach for manual guidance of industrial robots

This paper studies real-time manual guidance considering singularity and joint-limits avoidance using impedance control in an industrial scenario. The operator is responsible for keeping the end-effector (EE) away from the robot’s singularity and joint-limits. The proposed approach detects the singularity and joint-limits in real-time. Then, virtual stiffness and damping are added to target stiffness and damping as the robot is getting close to the singularity or joint-limit. A criterion is presented for detection of singularity by combining manipulability ellipsoid and condition number. Also a new joint to Cartesian space transformation is formulated in order to convert joint stiffness and damping to Cartesian stiffness and damping for joint-limits avoidance method. The presented approach is applied on a SCARA robot. An experiment is performed in this paper to investigate singularity and joint-limits avoidance separately as well as together. Increase in stiffness and damping warn the operator of the possibility of singularity or joint-limits allowing the operator to changes the EE path. The proposed approach, eliminates the need for a robotics expert by allowing any operator with no knowledge about robot singularity and joint-limits to interact and teach the robot in a safe, real-time and time-saving manner.     

On the Passivity-Based Impedance Control of Flexible Joint Robots

In this paper, a novel type of impedance controllers for flexible joint robots is proposed. As a target impedance, a desired stiffness and damping are considered without inertia shaping. For this problem, two controllers of different complexity are proposed. Both have a cascaded structure with an inner torque feedback loop and an outer impedance controller. For the torque feedback, a physical interpretation as a scaling of the motor inertia is given, which allows to incorporate the torque feedback into a passivity-based analysis. The outer impedance control law is then designed differently for the two controllers. In the first approach, the stiffness and damping terms and the gravity compensation term are designed separately. This outer control loop uses only the motor position and velocity, but no noncollocated feedback of the joint torques or link side positions. In combination with the physical interpretation of torque feedback, this allows us to give a proof of the asymptotic stability of the closed-loop system based on the passivity properties of the system. The second control law is a refinement of this approach, in which the gravity compensation and the stiffness implementation are designed in a combined way. Thereby, a desired static stiffness relationship is obtained exactly. Additionally, some extensions of the controller to viscoelastic joints and to Cartesian impedance control are given. Finally, some experiments with the German Aerospace Center (DLR) lightweight robots verify the developed controllers and show the efficiency of the proposed control approach.     

手功能康复机器人的鲁棒控制研究

以手功能康复机器人为研究对象,对被控对象建立数学模型,推导鲁棒控制器,基于simMechanics建立仿真模型,实现手功能康复机器人的鲁棒控制系统。考虑到手功能康复机器人是帮助偏瘫患者进行康复训练并最大限度地诱发患肢的主动作用,控制器中加入偏瘫患者的主动作用函数。控制系统在MATLAB／Simulink的环境下仿真,结果表明所设计的鲁棒控制器能适应不同程度的偏瘫患者,具有较佳的动态特性和很强的鲁棒性能。     

Optimal impedance control based on body inertia for a hydraulically driven hexapod robot walking on uneven and extremely soft terrain

This paper presents the implementation of impedance control for a hydraulically driven hexapod robot named COMET‐IV, which can walk on uneven and extremely soft terrain. To achieve the dynamic behavior of the hexapod robot, changes in center of mass and body attitude must be taken into consideration during the walking periods. Indirect force control via impedance control is used to address these issues. Two different impedance control schemes are developed and implemented: single‐leg impedance control and center of mass‐‐based impedance control. In the case of single‐leg impedance control, we derive the necessary impedance and adjust parameters (mass, damping, and stiffness) according to the robot legs' configuration. For center of mass–based impedance control, we use the sum of the forces of the support legs as a control input (represented by the body's current center of mass) for the derived impedance control and adjust parameters based on the robot body's configuration. The virtual forces from the robot body's moment of inertia are adapted to achieve optimal control via a linear quadratic regulator method for the proposed indirect attitude control. In addition, a compliant switching mechanism is designed to ensure that the implementation of the controller is applicable to the tripod sequences of force‐based walking modules. Evaluation and verification tests were conducted in the laboratory and the actual field with uneven terrain and extremely soft surfaces. © 2011 Wiley Periodicals, Inc.     

sEMG-based impedance control for lower-limb rehabilitation robot

Recently, various rehabilitation robots have been developed for therapeutic exercises. Additionally, several control methods have been proposed to control the rehabilitation robots based on user’s motion intention. One of the common control methods used is torque-based impedance control. This paper presents an electromyogram-based robust impedance control for a lower-limb rehabilitation robot using a voltage-based strategy. The proposed control strategy uses surface electromyogram (sEMG) signals in place of force sensors to estimate the exerted force. In addition, the control is based on the voltage control strategy, which differs from the common torque control strategies. For example, unlike the torque-based impedance control, the controller is not dependent on the dynamical models of the patient and the robot. This is particularly important as the dynamic of the patient is both difficult to model precisely and changes during the rehabilitation period. These simplifications results in a significant reduction in calculation time. To illustrate the effectiveness of the control approach, a 1-DOF lower-limb rehabilitation robot is designed. Experimental sEMG-force data are collected and used to train an artificial neural network. Simulation results show that compared with a torque-based control approach, the voltage-based is simpler, less computational and more efficient while it considers the presence of actuators. Finally, we design an adaptive fuzzy system to estimate and compensate the uncertainty in performing the impedance rule. The adaptive fuzzy system has an advantage that does not need new feedback to estimate the uncertainty. The control approach is further verified by stability analysis. Simulation results show the efficiency of the control approach in performing some therapeutic exercises.     

Smooth control of an articulated mobile robot with switching constraints

The paper describes a smooth controller of an articulated mobile robot with switching constraints. The use of switching constraints associated with grounded/lifted wheels is an effective method of controlling various motions; e.g. the avoidance of a moving obstacle. A model of an articulated mobile robot that has active and passive wheels and active joints with switching constraints is derived. A controller that accomplishes the trajectory tracking of the robot’s head and subtasks using smooth joint input is proposed on the basis of the model. Simulations and experiments are presented to show the effectiveness of the proposed controller.     

A Human-Robot Collaboration Framework for Improving Ergonomics During Dexterous Operation of Power Tools

In this work, we present a novel control approach to human-robot collaboration that takes into account ergonomic aspects of the human co-worker during power tool operations. The method is primarily based on estimating and reducing the overloading torques in the human joints that are induced by the manipulated external load. The human overloading joint torques are estimated and monitored using a whole-body dynamic state model. The appropriate robot motion that brings the human into the suitable ergonomic working configuration is obtained by an optimisation method that minimises the overloading joint torques. The proposed optimisation process includes several constraints, such as the human arm muscular manipulability and safety of the collaborative task, to achieve a task-relevant optimised configuration. We validated the proposed method by a user study that involved a human-robot collaboration task, where the subjects operated a polishing machine on a part that was brought to them by the collaborative robot. A statistical analysis of ten subjects as an experimental evaluation of the proposed control framework is provided to demonstrate the potential of the proposed control framework in enabling ergonomic and task-optimised human-robot collaboration.     

Reaching for redundant arms with human-like motion and compliance properties

This work proposes a redundant arm torque controller for reaching, guaranteeing desired completion time and accuracy requirements without the need for trajectory planning and prior knowledge of robot dynamics. The proposed controller is designed based on the prescribed performance control methodology and it is a reaching regulator in which the target pose for the hand acts as an attractor for the arm. It provides configuration consistency in return motions and hand and joint velocity smoothness. Its use in an admittance control scheme given measurements or estimates of external forces is also proposed providing active compliance capabilities in robot–environment interactions. Simulation studies for a 5dof human arm-like robot and experiments with a 7dof arm are performed to verify the approach and demonstrate the proposed controller’s performance.     

Development of a compliance controller to reduce energy consumption for bipedal robots

In this paper a strategy is proposed to combine active trajectory tracking for bipedal robots with exploiting the natural dynamics by simultaneously controlling the torque and stiffness of a compliant actuator. The goal of this research is to preserve the versatility of actively controlled humanoids, while reducing their energy consumption. The biped Lucy, powered by pleated pneumatic artificial muscles, has been built and controlled and is able to walk up to a speed of 0.15 m/s. The pressures inside the muscles are controlled by a joint trajectory tracking controller to track the desired joint trajectories calculated by a trajectory generator. However, the actuators are set to a fixed stiffness value. In this paper a compliance controller is presented to reduce the energy consumption by controlling the stiffness. A mathematical formulation has been developed to find an optimal stiffness setting depending on the desired trajectory and physical properties of the system and the proposed strategy has been validated on a pendulum structure powered by artificial muscles. This strategy has not been implemented on the real robot because the walking speed of the robot is currently too slow to benefit already from compliance control.

Control System Design for an Upper-Limb Rehabilitation Robot

Control system implementation is one of the major difficulties in rehabilitation robot design. The purpose of our study is to present newly developed control strategies for an upper-limb rehabilitation robot. The Barrett WAM Arm manipulator is used as the main hardware platform for the functional recovery training of the past-stroke patient. Passive and active recovery training have been implemented on the WAM Arm. A fuzzy-based PD position control strategy is proposed for the passive recovery exercise to control the WAM Arm stably and smoothly to stretch the impaired limb to move along predefined trajectories. An adaptive impedance force controller is employed in the active motion mode in which a fuzzy logic regulator is used to adjust the desired impedance between the robot and impaired limb to generate adaptive force in agreement with the change of the impaired limb's muscle strength. In order to evaluate the change of the impaired limb's muscle power, the impaired limb's mechanical impedance parameters as an objective evaluation index is estimated online by using a recursive least-squares algorithm with an adaptive forgetting factor. Experimental results demonstrate the effectiveness and potential of the proposed control strategies.     

基于无模型自适应的外骨骼式上肢康复机器人主动交互训练控制方法

设计了一种基于无模型自适应的外骨骼式上肢康复机器人主动交互训练控制方法.在机器人与人体上肢接触面安装力传感器采集人机交互力矩信息作为量化的主动运动意图,设计了一种无模型自适应滤波算法使交互力矩变得平滑而连贯;以人机交互力矩为输入,综合考虑机器人末端点与参考轨迹的相对位置和补偿力的信息,设计了人机交互阻抗控制器,用于调节各关节的给定目标速度;设计了将无模型自适应与离散滑模趋近律相结合的速度控制器完成机器人各关节对目标速度的跟踪.仿真结果表明,该控制方法可以实现外骨骼式上肢康复机器人辅助患者完成主动交互训练的功能.通过调节人机交互阻抗控制器的相应参数,机器人可以按照患者的运动意图完成不同的主动交互训练任务,并在运动出现偏差时予以矫正.控制器在设计实现过程中不要求复杂准确的动力学建模和参数识别,并有一定的抗干扰性和通用性.     

机器人串联弹性关节驱动器的刚度控制方法

机器人关节的柔顺性在人机协作过程中具有重要作用，然而固定的关节柔性无法满足动态变化的人机协作需求，因此对机器人的关节驱动器提出了具有刚度调节能力的要求.本文采用阿基米德螺旋线平面涡卷弹簧作为机器人关节的柔性元件，并提出一种可用于具有固定刚度的串联弹性驱动器的刚度控制方法.根据关节刚度的定义，将测量得到的弹簧输出端角度用于计算弹簧的输入端转角，使得机器人关节驱动器的等效刚度可以被调整到所期望的大小.该方法以电机位置控制为内环，关节刚度控制为外环，简化了控制器设计，并实现了解耦控制.对所设计的刚度控制器进行了分析.最后在自主设计的单自由度薄型串联弹性驱动器实验平台上进行了刚度调节实验，包括刚度的双向阶跃、零刚度和正弦变化的刚度，实验结果表明关节等效刚度能准确跟踪期望值，验证了该方法的有效性.     

Dynamic modeling,stability and energy consumption analysis of a realistic six-legged walking robot

This paper deals with a detailed analysis on kinematics, dynamics, stability and energy consumption of a realistic six-legged robot. The aim of this study is to extend a previous work of Roy et al. [1], in order to estimate optimal feet forces and joint torques of the six-legged robot generating wave-gaits with four different duty factors and deal with its stability issues. Two different approaches are developed to determine optimal feet forces. In the first approach, minimization of the norm of feet forces is carried out using a least square method, whereas minimization of the norm of joint torques is performed in the second approach. The second approach is found to be more energy efficient compared to the first one. The maximum values of feet forces and joint torques are seen to decrease with the increase of duty factor. The effects of walking parameters, namely velocity, stroke and duty factors have been studied on energy consumption and stability of the robot. The variations of average power consumption and specific energy consumption with the velocity and stroke are compared for four different duty factors. Wave gait with a low duty factor is found to be more energy-efficient compared to that with a high duty factor at the highest possible velocity.