Robot Force Control Research Articles

Control de Fuerza de Robots Manipuladores Basado en Observadores Proporcionales Integrales Generalizados

In this work the design of a linear observer–linear controller robust output feedback scheme is introduced for simultaneous trajectory tracking of position and force in fully actuated robot manipulators. The unknown state–dependent additive nonlinearity influencing the input–output description is modeled as an absolutely bounded “time–varying perturbation”. Generalized Proportional Integral (GPI) observers are shown to naturally estimate the unknown perturbation and a certain number of its time derivatives in an arbitrarily close manner. This information is used to advantage on the linear feedback controller design via a simple cancelation effort. To the best of the authors’ knowledge GPI observers have not been used before for robot force control. A comparison experimental analysis is presented to show the good performance of the proposed approach.

Stable Force Control of Industrial Robot Based on Spring Ratio and Instantaneous State Observer

Stable Force Control of Industrial Robot Based on Spring Ratio and Instantaneous State Observer

Toward Standardized Acoustic Radiation Force (ARF)-Based Ultrasound Elasticity Measurements With Robotic Force Control.

Acoustic radiation force (ARF)-based approaches to measure tissue elasticity require transmission of a focused high-energy acoustic pulse from a stationary ultrasound probe and ultrasound-based tracking of the resulting tissue displacements to obtain stiffness images or shear wave speed estimates. The method has established benefits in biomedical applications such as tumor detection and tissue fibrosis staging. One limitation, however, is the dependence on applied probe pressure, which is difficult to control manually and prohibits standardization of quantitative measurements. To overcome this limitation, we built a robot prototype that controls probe contact forces for shear wave speed quantification. The robot was evaluated with controlled force increments applied to a tissue-mimicking phantom and in vivo abdominal tissue from three human volunteers. The root-mean-square error between the desired and measured forces was 0.07 N in the phantom and higher for the fatty layer of in vivo abdominal tissue. The mean shear wave speeds increased from 3.7 to 4.5 m/s in the phantom and 1.0 to 3.0 m/s in the in vivo fat for compressive forces ranging from 2.5 to 30 N. The standard deviation of shear wave speeds obtained with the robotic approach were low in most cases ( 0.2 m/s) and comparable to that obtained with a semiquantitative landmark-based method. Results are promising for the introduction of robotic systems to control the applied probe pressure for ARF-based measurements of tissue elasticity. This approach has potential benefits in longitudinal studies of disease progression, comparative studies between patients, and large-scale multidimensional elasticity imaging.

Whole-body hierarchical motion and force control for humanoid robots

Robots acting in human environments usually need to perform multiple motion and force tasks while respecting a set of constraints. When a physical contact with the environment is established, the newly activated force task or contact constraint may interfere with other tasks. The objective of this paper is to provide a control framework that can achieve real-time control of humanoid robots performing both strict and non strict prioritized motion and force tasks. It is a torque-based quasi-static control framework, which handles a dynamically changing task hierarchy with simultaneous priority transitions as well as activation or deactivation of tasks. A quadratic programming problem is solved to maintain desired task hierarchies, subject to constraints. A generalized projector is used to quantitatively regulate how much a task can influence or be influenced by other tasks through the modulation of a priority matrix. By the smooth variations of the priority matrix, sudden hierarchy rearrangements can be avoided to reduce the risk of instability. The effectiveness of this approach is demonstrated on both a simulated and a real humanoid robot.

Learning Robot Force/Position Control for Repetitive High Speed Applications with Unknown Non–Linear Contact Stiffness

AbstractThis paper proposes a learning robot force/position control for high speed force trajectory following. Following high speed force trajectories in different repetitve robotic applications is a challenging field in robot force control. If the end–effector should provide a contact force while following a position trajectory in the non–force controlled direction a parallel force / position control is suitable. However, when it comes to high speed tasks this force control method reaches its limit. The problem can be solved by using an iterative learning control method in combination with the parallel force/position control. In this paper the learning force control method is introduced and experimental results are presented. (© 2015 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Hybrid motion/force control of multi-backbone continuum robots

The recent growth of surgical applications exploiting continuum robots demands for new control paradigms that ensure safety by controlling interaction forces of tele-operated end-effectors. In this paper, we present the modeling, sensing and control of multi-backbone continuum robots in a unified framework for hybrid motion/force control. Multi-backbone continuum robots allow to estimate forces and torques at the operational point by monitoring loads along their actuation lines without the need for a dedicated transducer at the operational point. This capability is indeed crucial in emerging fields such as robotic surgery where cost and strict sterilization guidelines prevent the adoption of a dedicated sensor to provide force feedback from the sterile field. To advance further the force sensing capabilities of multi-backbone continuum robots, we present a new framework for hybrid motion and force control of continuum robots with intrinsic force sensing capabilities. The framework is based on a kinetostatic modeling of the multi-backbone continuum robot with, a simplified model for online estimate of the manipulator’s compliance, and a new strategy for merging force and motion control laws in the configuration space of the manipulator. Experimental results show the ability to sense and regulate forces at the operational point and evaluate the framework for shape exploration and stiffness imaging in flexible environments.

Neurofuzzy self-tuning of the dissipation rate gain for model-free force-position exponential tracking of robots

Simultaneous force and position control of robots interacting with a rigid environment has been broadly studied assuming several contact force models, being the differential algebraic – DAE – model the most complete one, however DAE robots show complex and strong nonlinear couplings that make difficult to achieve tracking, when dynamic model is not available. In this paper, considering the fundamental structural properties of DAE robots, in particular passivity and the orthogonalization of force and velocity vectors, it is proposed a model-free neurofuzzy-based self-tuning robot controller for exponential tracking, which is composed of orthogonalized PID-position plus an I-force (If) control terms, and a feed-forward desired force term. The salient feature of this proposal is a novel neurofuzzy self-tuning scheme aimed at tuning the dissipation rate gain (DRG) so as to enforce dissipativity in closed-loop, rather than the standard scheme of tuning the feedback control gains, or the control structure, which in our case stands for a simple constant feedback gain orthogonalized PID+If controller. In fact, in virtue of such orthogonalization, it emerges a simple and low cost parallel structure of the neuro-fuzzy network that targets solely the DRG so as to drive error dynamics to zero with exponential rate, without any knowledge of robot dynamics or carrying out any approximation of inverse dynamics. Thus, this technique can be applied to other class of systems and controllers that ensure passivity in closed-loop. Simulations show the validity and the feasibility of this new approach.

DOF Decoupling Task Graph Model: Reducing the Complexity of Touch-Based Active Sensing

This article presents: (i) a formal, generic model for active sensing tasks; (ii) the insight that active sensing actions can very often be searched on less than six-dimensional configuration spaces (bringing an exponential reduction in the computational costs involved in the search); (iii) an algorithm for selecting actions explicitly trading off information gain, execution time and computational cost; and (iv) experimental results of touch-based localization in an industrial setting. Generalizing from prior work, the formal model represents an active sensing task by six primitives: configuration space, information space, object model, action space, inference scheme and action-selection scheme; prior work applications conform to the model as illustrated by four concrete examples. On top of the mentioned primitives, the task graph is then introduced as the relationship to represent an active sensing task as a sequence of low-complexity actions defined over different configuration spaces of the object. The presented act-reason algorithm is an action selection scheme to maximize the expected information gain of each action, explicitly constraining the time allocated to compute and execute the actions. The experimental contributions include localization of objects with: (1) a force-controlled robot equipped with a spherical touch probe; (2) a geometric complexity of the to-be-localized objects up to industrial relevance; (3) an initial uncertainty of (0.4 m, 0.4 m, 2Π); and (4) a configuration of act-reason to constrain the allocated time to compute and execute the next action as a function of the current uncertainty. Localization is accomplished when the probability mass within a 5-mm tolerance reaches a specified threshold of 80%. Four objects are localized with final {mean; standard-deviation} error spanning from {0.0043 m; 0.0034 m} to {0.0073 m; 0.0048 m}.

Voltage-based adaptive impedance force control for a lower-limb rehabilitation robot

This paper presents a novel voltage-based adaptive impedance force control for a lower limb rehabilitation robot. The impedance parameters are adaptively regulated by a gradient descent algorithm for adjusting the human force in performing therapeutic exercises. Although the proposed control is based on voltage control strategy, it differs from the common torque control strategy. One of the advantages is that it is free from the dynamical models of the robot and patient. Compared with a torque control scheme, it is simpler, less computational, and more efficient while it considers the actuators. The control approach is verified by stability analysis. Simulation results show the efficiency of the control approach applied on a lower limb rehabilitation robot driven by an electric motor. A comparison on performing isometric exercise shows that the voltage-based adaptive impedance force control is superior to both voltage-based impedance control and torque-based impedance control.

Torque Estimation for Robotic Joint With Harmonic Drive Transmission Based on Position Measurements

Joint torque sensory feedback is an effective technique for achieving high-performance robot force and motion control. However, most robots are not equipped with joint torque sensors, and it is difficult to add them without changing the joint's mechanical structure. A method for estimating joint torque that exploits the existing structural elasticity of robotic joints with harmonic drive transmission is proposed in this paper. In the presented joint torque estimation method, motor-side and link-side position measurements along with a proposed harmonic drive compliance model, are used to realize stiff and sensitive joint torque estimation, without the need for adding an additional elastic body and using strain gauges to measure the joint torque. The proposed method has been experimentally studied and its performance is compared with measurements of a commercial torque sensor. The results have attested the effectiveness of the proposed torque estimation method.

유압식 로봇의 힘 제어를 위한 유압 서보 시스템의 특성에 관한 연구

유압식 로봇의 힘 제어를 위한 유압 서보 시스템의 특성에 관한 연구

Design and optimization of a novel six-axis force/torque sensor for space robot

With the development of Chinese space technology, the construction of Chinese Space Station (CSS) has been on the agenda. The space robot takes a critical function in the CSS. It is an important tool in completing space tasks such as on-orbit assembly, maintenance, manipulation assistance, payload care and astronaut on-orbit support. The six-axis force/torque sensor equipped on the space robot could sense the three orthogonal forces and torques simultaneously, which will play an important role in the force control of space robot. Considering the dimension and compatibility, we designed a novel six-axis force/torque sensor based on strain gauges for the space robot. Different with the traditional Maltese cross beam, it is a novel structure with through-hole beam. Compared with the usually optimization method by trial and error, employing the response surface methodology (RSM) to acquire the optimum dimensional parameters is proposed in this paper. To get the accurate positions of the strain gauges bonded on the elastic body, strain distribution analysis on path is adopted. In the end, the sensor is manufactured and the calibration system is developed. The experimental results show a good performance of nonlinearity, repeatability, stability, hysteresis, sensitivity, and accuracy.

High performance force control - A new approach and suggested benchmark tests

This paper is a report about the testing and evaluation of a special force control scheme for standard industrial robots. The working principle of the new force control scheme is described, and quantitative test results are presented. It was the authors’ intention to compare the results with those from other research groups, but this was not possible because of two main reasons: Firstly it turned out that only very few quantitative results about robot force control have been published, and secondly it became clear that the robotics community has not yet developed suitable benchmark tests for the assessment of a robot's force control capabilities and quality. In order to initiate a discussion and further activities in this area, a set of proposed benchmark tests is described in this paper. The usefulness of the benchmark tests is illustrated with some examples.

Research on Grinding and Polishing Force Control of Compliant Flange

The automation of the grinding and polishing process is important to improve the production efficiency of the part surfaces. In this paper, a new compliant flange mounted on the end of the industrial robots for the robotic grinding and polishing force control is developed. With regard to the non-linear and time-varying problem of the contact force, the mathematical model of the new force control system was presented and the fuzzy PID control strategy was used to drive the proposed system. Especially, the air spring and electric propor- tional valve is studied to establish the model. The simulation results show that the selected control strategy has quick response and good robustness, which satisfies the real-time requirements of the grinding and polishing force control in processing.

Design and Calibration of a Six-axis Force/torque Sensor with Large Measurement Range Used for the Space Manipulator

Multi-axis force/torque sensor is a key component for space robot force control and teleoperation. The special environment of space, however, brings huge challenges to the design of multi-axis force/torque sensor. In this paper, a six-axis force/torque sensor, which could be used as a component for the large manipulator in the space station, is developed. In order to obtain the large measurement range of force/torques, an elastic body based on cross-beam with anti-overloading capability is designed, and the size is optimized by using FEA to guarantee both high stiffness and sensitivity of the six-axis force/torque sensor. Different from the conventional method, the signal acquisition module which includes a high signal-to-noise ratio amplifier circuit is integrated in the sensor so as to be more reliable. Then, a novel calibration system is designed to provide large and accurate force/torque source. According to the particularity of the sensor's coupling errors, two decoupling algorithms are proposed in this paper to achieve high precision and flexible usage. The online decoupling algorithm is based on calculating decoupling matrices in partitioned space, while the offline algorithm is based on an optimized BP Neural Network using GA. Experimental results show that the designed six-axis force/torque sensor works well with high precision and reliability.

Dynamic Modeling and Force Control of a Redundant Robot for Polishing Applications

AbstractFor many robotic applications with tasks such as cutting, assembly or polishing, it is necessary to get in contact with the surrounding. In this paper a redundant robot with seven degrees of freedom in a metal polishing task is considered. For simulation as well as for the controller design a dynamic model of the robot and a contact model are required. The equations of motion of the robot are calculated with the Projection Equation in subsystem representation and the contact model contains linear tool elasticities and work piece elasticities. In the case of a polishing task, a constant contact force during the process is required even if the robot moves along a trajectory. Thus some degrees of freedom of the robot tool center point have to be position controlled while the other ones have to be force controlled. The redundant robot offers the possibility to avoid singular positions or to maximize the available end‐effector forces within the inverse kinematics and is therefore best suited for polishing large objects. The actual process forces are measured with a six axis force‐torque‐sensor mounted at the tool center point. These forces are used in a parallel force/position control law to achieve the desired behavior. Results from measurements of a test arrangement are presented. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Hybrid force control of astronaut rehabilitative training robot under active loading mode

In order to mitigate the effects of space adaptation syndrome (SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot (ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit (CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.

Introducing fundamental concepts of control: A case study in robot force control

This paper describes an approach to teaching concepts of automatic control, aimed principally at mechanical engineering students on courses that do not include a dedicated control module. The application area employed is robot force control, which has been the focus of much research during the past three or more decades. In this work, a robot is modelled in MATLAB and Simulink as a simple one degree-of-freedom ‘arm’, which is based on a velocity-controlled DC motor. The paper describes the development of this model and how it can be approximated as a standard second-order system from step response data. Three example solutions for designing a suitable force controller are then discussed, for a situation where the stiffness of contact at the robot/task interface is known and constant. The approach can be used in conjunction with a more traditional course in automatic control, or act as standalone tutorial for those with a more specific interest in force control.

Dynamic Modeling and Model-Based Force Control of a 3-DOF Translational Parallel Robot

A 3-axis parallel loading mechanism, which works as a multi-axis load simulator, is proposed for reliability test of multi-axis CNC machine tools by exerting specific load spectrums on the spindle. To achieve efficient loading force control, dynamic model of the 3-DOF translational parallel robot is derived via the virtual work principle and is embedded into the control strategy to build a model-based control scheme. A mass distribution factor is introduced and the rotating inertia of the limbs is neglected to simplify the dynamics equations for better real-time control performance. This simplification method is verified by comparison with the complete dynamics model. Then the simplified dynamic model is integrated with a PI (proportional–integral) controller with feedforward to control the moving platform’s output force in the task space and this control strategy is verified through co-simulations with MATLAB/Simulink and ADAMS. Simulation results show that the proposed model-based PI controller is effective to control the three-dimensional output force of the 3-DOF translational parallel robot.

A double-loop structure in the adaptive generalized predictive control algorithm for control of robot end-point contact force

Robot force control is an essential issue in robotic intelligence. There is much high uncertainty when robot end-effector contacts with the environment. Because of the environment stiffness effects on the system of the robot end-effector contact with environment, the adaptive generalized predictive control algorithm based on quantitative feedback theory is designed for robot end-point contact force system. The controller of the internal loop is designed on the foundation of QFT to control the uncertainty of the system. An adaptive GPC algorithm is used to design external loop controller to improve the performance and the robustness of the system. Two closed loops used in the design approach realize the system׳s performance and improve the robustness. The simulation results show that the algorithm of the robot end-effector contacting force control system is effective.