Compliance and Force Control for Computer Controlled Manipulators

Compliant motion occurs when the manipulator position is constrained by the task geometry. Compliant motion may be produced either by a passive mechanical compliance built in to the manipulator, or by an active compliance implemented in the control servo loop. The second method, called force control, is the subject of this report. In particular, this report presents a theory of force control based on formal models of the manipulator, and the task geometry. The ideal effector is used to model the manipulator, and the task geometry is modeled by the ideal surface, which is the locus of all positions accessible to the ideal effector. Models are also defined for the goal trajectory, position control, and force control.

Predictive position and force control for shape memory alloy cylinders

In this paper, a linear lightweight electric cylinder constructed using shape memory alloy (SMA) is proposed. Spring SMA is used as the actuator to control the position and force of the cylinder rod. The model predictive control algorithm is investigated to compensate SMA hysteresis phenomenon and control the cylinder. In the predictive algorithm, the future output of the cylinder is computed based on the cylinder model, and the control signal is computed to minimize the error and power criterion. The cylinder model parameters are estimated by an online identification algorithm. Experimental results show that the SMA cylinder is able to precisely control position and force by using the predictive control strategy though the hysteresis effect existing in the actuator. The performance of the proposed controller is compared with that of a conventional PID controller

Modeling Robot Dynamic Performance for Endpoint Force Control

This research aims to understand the fundamental dynamic behavior of servo-controlled machinery in response to various types of sensory feedback. As an example of such a system, we study robot force control, a scheme which promises to greatly expand the capabilities of industrial robots by allowing manipulators to interact with uncertain and dynamic tasks. Dynamic models are developed which allow the effects of actuator dynamics, structural flexibility, and workpiece interaction to be explored in the frequency and time domains. The models are used first to explain the causes of robot force control instability, and then to find methods of improving this performance.

Trajectory and Force Control of a Direct Drive Arm

Using the MIT Serial Link Direct Drive Arm as the main experimental device, various issues in trajectory and force control of manipulators were studied in this thesis. Since accurate modeling is important for any controller, issues of estimating the dynamic model of a manipulator and its load were addressed first. Practical and effective algorithms were developed fro the Newton-Euler equations to estimate the inertial parameters of manipulator rigid-body loads and links. Load estimation was implemented both on PUMA 600 robot and on the MIT Serial Link Direct Drive Arm. With the link estimation algorithm, the inertial parameters of the direct drive arm were obtained. For both load and link estimation results, the estimated parameters are good models of the actual system for control purposes since torques and forces can be predicted accurately from these estimated parameters. The estimated model of the direct drive arm was them used to evaluate trajectory following performance by feedforward and computed torque control algorithms. The experimental evaluations showed that the dynamic compensation can greatly improve trajectory following accuracy. Various stability issues of force control were studied next. It was determined that there are two types of instability in force control. Dynamic instability, present in all of the previous force control algorithms discussed in this thesis, is caused by the interaction of a manipulator with a stiff environment. Kinematics instability is present only in the hybrid control algorithm of Raibert and Craig, and is caused by the interaction of the inertia matrix with the Jacobian inverse coordinate transformation in the feedback path. Several methods were suggested and demonstrated experimentally to solve these stability problems. The result of the stability analyses were then incorporated in implementing a stable force/position controller on the direct drive arm by the modified resolved acceleration method using both joint torque and wrist force sensor feedbacks.

Joint servoing for robust manipulator force control

An experimental and theoretical comparison is made of force control performance with different types of innerloop joint servoing techniques. The problem of disturbance rejection and sensitivity to plant dynamics variations (robustness) is addressed. Position, velocity, strain gauge derived joint torque, and current servos are designed and implemented on a specially instrumented industrial robot, and the end-effector force feedback performances achieved are compared. Joint strain derived torque servoing is found to provide the best overall robust force control performance. Experimental results of the robust hard-on-hard contact achieved with the novel force controller implementation based on joint torque sensing are provided. Conclusions are drawn on the force control performance achievable on a geared robot given the joint servoing technique.

Models of passive and active dendrite motoneuron pools and their differences in muscle force control

Motoneuron (MN) dendrites may be changed from a passive to an active state by increasing the levels of spinal cord neuromodulators, which activate persistent inward currents (PICs). These exert a powerful influence on MN behavior and modify the motor control both in normal and pathological conditions. Motoneuronal PICs are believed to induce nonlinear phenomena such as the genesis of extra torque and torque hysteresis in response to percutaneous electrical stimulation or tendon vibration in humans. An existing large-scale neuromuscular simulator was expanded to include MN models that have a capability to change their dynamic behaviors depending on the neuromodulation level. The simulation results indicated that the variability (standard deviation) of a maintained force depended on the level of neuromodulatory activity. A force with lower variability was obtained when the motoneuronal network was under a strong influence of PICs, suggesting a functional role in postural and precision tasks. In an additional set of simulations when PICs were active in the dendrites of the MN models, the results successfully reproduced experimental results reported from humans. Extra torque was evoked by the self-sustained discharge of spinal MNs, whereas differences in recruitment and de-recruitment levels of the MNs were the main reason behind torque and electromyogram (EMG) hysteresis. Finally, simulations were also used to study the influence of inhibitory inputs on a MN pool that was under the effect of PICs. The results showed that inhibition was of great importance in the production of a phasic force, requiring a reduced co-contraction of agonist and antagonist muscles. These results show the richness of functionally relevant behaviors that can arise from a MN pool under the action of PICs.

Visuomotor processing and hand force coordination in dyslexic children during a visually guided manipulation task

Developmental Dyslexia negatively affects children's reading and writing ability and, in most cases, performance in sensorimotor tasks. These deficits have been associated with structural and functional alterations in the cerebellum and the posterior parietal cortex (PPC). Both neural structures are active during visually guided force control and in the coordination of load force (LF) and grip force (GF) during manipulation tasks. Surprisingly, both phenomena have not been investigated in dyslexic children. Therefore, the aim of this study was to compare dyslexic and non-dyslexic children regarding their visuomotor processing ability and GF-LF coordination during a static manipulation task. Thirteen dyslexic (8-14YO) and 13 age- and sex-matched non-dyslexic (control) children participated in the study. They were asked to grasp a fixed instrumented handle using the tip of all digits and pull the handle upward exerting isometric force to match a ramp-and-hold force profile displayed in a computer monitor. Task performance (i.e., visuomotor coordination) was assessed by RMSE calculated in both ramp and hold phases. GF-LF coordination was assessed by the ratio between GF and LF (GF/LF) calculated at both phases and the maximum value of a cross-correlation function (r(max)) and its respective time lag calculated at ramp phase. The results revealed that the RMSE at both phases was larger in dyslexic than in control children. However, we found that GF/LF, rmax, and time lags were similar between groups. Those findings indicate that dyslexic children have a mild deficit in visuomotor processing but preserved GF-LF coordination. Altogether, these findings suggested that dyslexic children could present mild structural and functional alterations in specific PPC or cerebellum areas that are directly related to visuomotor processing. (C) 2014 Elsevier Ltd. All rights reserved.

Movement control of manipulative tasks in patients with Gilles de la Tourette syndrome

When a hand-held object is moved, grip and load force are accurately coordinated for establishing grasp stability. In the present work, the question was raised whether patients with Gilles de la Tourette syndrome (TS), who show tic-like movements, are impaired in grip-load force control when executing a manipulative task. To this end, we assessed force regulation during action patterns that required rhythmical unimanual or bimanual (iso-directional/anti-directional) movements. Results showed that the profile of grip-load force ratio was characterized by maxima and minima that were realized at upward and downward hand positions, respectively. TS patients showed increased force ratios during unimanual and bimanual movements, compared with control subjects, indicative of an inaccurate specification of the precision grip. Functional imaging data complemented the behavioural results and revealed that secondary motor areas showed no (or greatly reduced) activation in TS patients when executing the movement tasks as compared with baseline conditions. This indicates that the metabolic level in the secondary motor areas was equal during rest and task performance. At the neuronal level, this observation suggests that these cortical areas were continuously involved in movement preparation. Based on these data, we conclude that the ongoing activation of secondary motor areas may be explained by the TS patients' involuntary urges to move. Accordingly, interference will prevent an accurate planning of voluntary behaviour. Together, these findings reveal modulations in movement organization in patients with TS and exemplify degrading consequences for manual function.

Force-controlled automatic microassembly of tissue engineering scaffolds

This paper presents an automated system for 3D assembly of tissue engineering (TE) scaffolds made from biocompatible microscopic building blocks with relatively large fabrication error. It focuses on the pin-into-hole force control developed for this demanding microassembly task. A beam-like gripper with integrated force sensing at a 3 mN resolution with a 500 mN measuring range is designed, and is used to implement an admittance force-controlled insertion using commercial precision stages. Visual-based alignment followed by an insertion is complemented by a haptic exploration strategy using force and position information. The system demonstrates fully automated construction of TE scaffolds with 50 microparts whose dimension error is larger than 5%.

Force controlled hexapod walking

In this paper we describe the dynamic simulation of an 18 degrees of freedom hexapod robot with the objective of developing control algorithms for smooth, efficient and robust walking in irregular terrain. This is to be achieved by using force sensors in addition to the conventional joint angle sensors as proprioceptors. The reaction forces on the feet of the robot provide the necessary information on the robots interaction with the terrain. As a first step we validate the simulator by implementing movement control by joint torques using PID controllers. As an unexpected by-product we find that it is simple to achieve robust walking behaviour on even terrain for a hexapod with the help of PID controllers and by specifying a trajectory of only a few joint configurations.

Modeling and position-sensorless control of a dual-airgap axial flux permanent magnet machine for flywheel energy storage systems

This paper presents the modeling and position-sensorless vector control of a dual-airgap axial flux permanent magnet (AFPM) machine optimized for use in flywheel energy storage system (FESS) applications. The proposed AFPM machine has two sets of three-phase stator windings but requires only a single power converter to control both the electromagnetic torque and the axial levitation force. The proper controllability of the latter is crucial as it can be utilized to minimize the vertical bearing stress to improve the efficiency of the FESS. The method for controlling both the speed and axial displacement of the machine is discussed. An inherent speed sensorless observer is also proposed for speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a prototype machine.