Fuzzy Predictive Algorithms Applied to Force Control of Robotic Manipulators

When a robot performs the same task repeatedly, a learning controller can enhance the performance of the system significantly. The function of the learning controller is to update the feedforward compensator which cancels the dynamics of robot manipulators and friction of each joints. The feedforward compensator especially plays an important role in the contact force control of robot manipulators with rigid workpiece since it allows more compliance in the force control direction as the force feedback gain is reduced. In this paper, the learning algorithm which guarantees the asymptotic stability is studied and applied to refine the feedforward compensator. Experiments with two degree of freedom direct drive robot confirm the effectiveness of the algorithm.

This paper presents a unified control framework for both set-point and time-varying force control of robot manipulator by introducing an improved position-based impedance control (IPBIC). In order to essentially achieve accurate force control, especially time-varying force tracking, a new target impedance function compensated by a force controller is presented. The essence of the improved method in realizing time-varying force tracking, as well as the coupled stability of the manipulator–environment system is investigated. To further improve the force control performance, the Newton-type iterative learning control (ILC) is introduced upon the closed-loop system. A case study on a two-link robot model demonstrates the effectiveness of this method.

A new classification scheme for robotic force control algorithms is presented. It is shown that algorithms can be categorized according to whether they are joint-based or cartesian-based. Further, they can be grouped according to whether the innermost servo loop is based on torque, velocity, or position. For useful force control, closing an inner loop on position can greatly increase disturbance rejection while also allowing for a split rate servo controller to minimize the computational burden. Experimental results from the implementation of a new force feedback method are presented. This cartesian-based method uses an inner loop closed on position and has been implemented on an AdeptOne robot. Bias force application, force searching, and selective compliance about a synthetic remote center compliance (RCC) have all been implemented. Excellent results in free space and in hard contact have been achieved. This technique has been successfully used to assemble parts having 0.001 inch clearances.

This paper presents an experimental evaluation and comparison of basic strategies that have been proposed for force control of robot manipulators. This experimental review of force control methodologies is unique in its breadth - never has such a complete spectrum of strategies been experimentally compared on the same system. The commonality amongst the experiments has permitted the ability to objectively compare and contrast these strategies, and draw conclusions about the efficacy of each. As will be seen, the results support our previous analysis and show the superiority of integral force control for force trajectory tracking.

This article presents a comparative study between the hybrid impedance control approach and the impedance force control approach with neural networks compensation of manipulator modeling errors. The proposed algorithm consists of an outer hybrid impedance control loop that generates the reference (target) acceleration to an inner inverse dynamics control loop. In order to improve the controller robustness, a compensation action of the manipulator modeling errors is introduced, acting on the target acceleration. This compensation action is based on a neural network model achieved by minimizing the modeling errors along the manipulator trajectory. The neural network algorithm uses an error training signal to model errors, that is minimized along the trajectory. The performance of the hybrid impedance control system with neural network compensation, is compared with the impedance force controller with neural network compensation, and is illustrated by computer simulations with a two degree-of-freedom PUMA 560 robot, whose end-effector is forced to move along a frictionless surface located perpendicular to the horizontal plane. The results obtained reveal even better performance when the desired force profile is not constant along the trajectory. This situation is very important in fine motion tasks where the desired force must have a varying profile along the trajectory, namely at the beginning and the end of the task. The results have also shown accurate force tracking and position control, even when significant uncertainties in the robot dynamic model are assumed.

Some types of learning control were developed for a class of robot manipulators to realize a desired motion. In those control schemes, the actuator input to the robot is modified by the acceleration error signal or the velocity error signal so as to make the robot motion approach the desired one by repeating operation of the robot. However, since actual measured signals of those variables are apt to be contaminated by noise, it is desirable to correct the input by an actual position signal which is more accurately measured than the acceleration or velocity signal. Motivated by this observation, a new type of learning control is proposed, in which the input is modified by the position error signal. It is theoretically shown that by using this control method the robot motion converges to the desired one with repetition of maneuvering the robot. It is also shown that this learning method can be applied to not only position control but also force control of robot manipulators. Moreover, it is experimentally shown by using such a learning method that the real robot can be trained to polish a curved surface of an object and eventually carry the task to fulfillment.

11R8. Underwater Robots: Motion and Force Control of Vehicle-Manipulator Systems. Springer Tracts in Advanced Robotics, Vol 2. - G Antonelli (Dipartimento di Automazione, Elettromagnetismo, Ingegneria dell’Informazione e Matematica Industriale, Univ degli Studi di Cassino, Via di Biasio 43, Cassino, 03043, Italy). Springer-Verlag, Berlin. 2003. 183 pp. ISBN 3-540-00054-2. $89.95.Reviewed by M Pascal (LSC, Univ d’Evry Val d’Essonne, 40 rue du Pelvoux, 91020 Evry, France).The book originates from a PhD thesis defended by the author in 1999 at Naples University and is concerned by a new advance in robotics related to underwater vehicle-manipulator systems (UVMS). Several interesting applications of these systems can be found in industry and several models of autonomous underwater vehicles (AUV) are developed in various research centers. The design of control laws for underwater robots is a challenging task, owing to the complexity of the system and to the uncertainty in the model parameters, mainly due to the poor knowledge of the hydrodynamic effects. The implementation of standard control algorithms used for ground fixed manipulators is not easy and a necessary improvement of these control laws must be achieved to overcome all the drastic constraints of such systems. The book involves four chapters followed by two appendices and a wide list of references. A great number of figures of good quality are also included. Chapter 1 is devoted to mechanical modeling of underwater robots composed of a rigid body connected to a serial manipulator. Rigid body’s kinematics is recalled, with a special attention to attitude representation by quaternions. Standard models of hydrodynamic effects are briefly presented, and the kinematics of manipulators with mobile base is described by Denavit-Hartenberg method. The dynamical model of the system is expressed in matrix form and its linear dependence with respect to a set of dynamical parameters is underlined. At last, a simplified model of the reaction force applied to the effectors in the occurrence of contacts with the environment is presented. Chapter 2 deals with inverse kinematic resolution and kinematic control. An underwater vehicle-manipulator system is always redundant due to its mobile base. This redundancy is used in order to achieve both end effectors tracking trajectory and some other control objectives like avoiding singular configurations of the manipulator or energy savings. Several strategies of kinematic control are presented with special attention to the task priority approach and to an interesting application of fuzzy technique. These methods are applied on two models of UVMS and the corresponding numerical simulations seem to give promising results. In Chapter 3, the dynamic control of UVMS is investigated. The sliding mode control is first proposed and validated by numerical simulation on a special model with eight degrees of freedom. Several other methods are also presented and simulated, including adaptative control, output feedback control, and virtual decomposition based control. At the end of the chapter, experimental results are shown: these results originate from a set of experiments performed at the University of Hawaii on a special model of AUV developed in this institute. Tracking trajectory is investigated by using several kinds of adaptative controls. The performances of these control laws are compared in the presence of disturbances such as current effects, thrusters’ fault, and strong noise of the sensors measures. A new adaptative control is also proposed, based on dynamical compensation expressed in a reference frame with respect to which the disturbance is constant, and experiments performed with this method give rather good results. The last chapter introduces interaction control. A force control scheme without exact dynamical compensation is defined; the redundancy of the system is used to define a task priority inverse kinematics algorithm and suitable secondary tasks. Interesting numerical simulations are performed on a nine degree of freedom UVMS, showing the method’s efficiency. In conclusion, Underwater Robots: Motion and Force Control of Vehicle Manipulator Systems provides an interesting reference text about control of underwater robots. The monograph can be useful for researchers interested by this field or, more widely, for scientists involved in control of manipulators with mobile bases or mobile robots in three-dimensional space.

In this paper, model-based precision force and position control of an ionic polymer metal composite (IPMC) is presented. A 23.8 mm × 3.4 mm × 0.16 mm IPMC strip was used as an actuator in a cantilever configuration. Open-loop force and position responses of an IPMC are not repeatable, and hence closed-loop precision control is of critical importance to ensure proper functioning, repeat-ability and reliability. After feedback controllers were designed and implemented with empirically obtained fourth-order plant transfer functions, the overshoot decreased from 460 to 2.8 per cent and the settling time was reduced from 37.5 to 3.22 s in force control. In position control the overshoot decreased from 333 to 20.3 per cent and the settling time was reduced from 21.5 to 2.56 s. Microscale precision force and position control capabilities of the IPMC actuator were also demonstrated experimentally. An 8 μN force resolution was achieved with a force noise of 0.5μN r.m.s., and the position resolution was 6 μm with a position noise of 2.5 μm r.m.s. The maximum force and tip displacement achieved with the IPMC actuator under closed-loop control were 2 mN and 5 mm respectively. The IPMC actuator could follow various commanded force and position trajectories such as sinusoidal and trapezoidal position profiles, and a velocity profile with a 3 mm/s maximum velocity. A novel hybrid force and position control strategy demonstrated its utility in practical micromanipulalion applications where the actuator force must be limited to prevent damaging micro-objects. High-precision control of the IPMC at low force level proved its potential for micromanufacturing and micromanipulation applications such as robotic and biomedical microgrippers.

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International audience

Mainstream industrial practice of assembling different flexible wires into the connector is manual due to different specifications of terminals and flexible wire assembly requirements. Therefore, the efficiency of the production and the quality of the assembly rely heavily on the knowledge and experiences of human workers. To reduce the labor cost and possible errors, this paper presents an adaptive force and posture control strategy for automated wiring terminal assembly (WTA). The contact force states during the search phase and insertion phase are first analyzed and then modeled. With the force analysis, fuzzy-PID controllers are applied for translational and angular adjustment during the assembly process. To validate the control strategy proposed, a prototype system is set up by integrating a force/torque (F/T) sensor and cameras on an industrial robot. And two kinds of industrial wires with four types of different wire terminals are tested with comparative studies. The results have shown that the proposed control strategy is able to conduct automatic insertion with different flexible wires successfully with reliable force feedback.

The quadruped robot can achieve stable locomotion with contact force control. The crucial technique of it is to convert the control of the center of mass (COM) to the control of supporting legs. In this paper, we propose a force distribution and control strategy based on model decomposition and optimal contact constrains for the quadruped robot with trotting gait. The quadruped robot can be modeled as a virtual planar seven-link and a virtual planar three-link under the supposition that the control of the COM is decoupled. Meanwhile, an optimal contact constraint will be proposed and the desired contact force can be found. The simulation and experiment results show that the robot can track the desired trajectories exactly and steadily.

Application of μ theory in compliant force control system is studied. Compliant force control strategy is developed based on the inner loop position control of 6-DOF parallel robot in order to simulate pushing and pulling procedure of forcible alignment of space docking. The cascade structure of "out-force-loop containing inner-position-loop" is depicted, and the method is set forth using classical control strategy to realize compliant force control. Considering uncertainties such as parameter perturbations, model perturbations and external disturbances, etc, robust force controller is designed using μ synthesis theory. It is listed in detail that the selection method of weighting functions in robust compliant force control loop and the designing procedure of robust force controller. Robust stability and robust performance are compared between robust force controller and classical force controllers by μ analysis. Experiment of robust force controller and classical force controllers is presented. The results indicate that the designed robust force controller is of efficiency and superiority.

Haptic cues delivered via wearable devices have great potential to enhance a user's experience by transmitting task information and touch sensations in domains such as virtual reality, teleoperation, and prosthetics. Much is still unknown on how haptic perception, and consequently optimal haptic cue design, varies between individuals. In this work we present three contributions. First, we propose a new metric, the Allowable Stimulus Range (ASR), as a way to capture subject-specific magnitudes for a given cue, using the method of adjustments and the staircase method. Second, we present a modular, grounded, 2-DOF, haptic testbed designed to conduct psychophysical experiments in multiple control schemes and with rapidly-interchangeable haptic interfaces. Third, we demonstrate an application of the testbed and our ASR metric, together with just noticeable differences (JND) measurements, to compare perception of haptic cues delivered via position or force control schemes. Our findings show that users demonstrate higher perceptual resolution in the position-control case, though survey results suggest that force-controlled haptic cues are more comfortable. The results of this work outline a framework to define perceptible and comfortable cue magnitudes for an individual, providing the groundwork to understand haptic variability, and compare the effectiveness of different types of haptic cues.