Dynamic Force Compensation Research Articles

Force-free control of low drag resistance for humanoid robot joint

A method for the force-free control of humanoid robot joints is presented that meets human–machine cooperation functions of a humanoid robot. To ensure accurate torque control, the current loop of the permanent magnet synchronous motor was initially optimised and its dynamic response improved with a compensating back electromotive force. The motor speed is then estimated by sampling the voltage and current, the values of which are used in the calculation of the joint angle and the gravitational-force compensation. Finally, a method to evaluate the dynamic force compensation is applied that then yields the motor output offset, the total gravitational load, the partial inertia force, and the partial friction moment. Experimental results show that this method reduces the drag torque to less than 1 Nm. This method can be widely applied to a variety of robotic joints.

Research on Collision Point Identification Based on Six-Axis Force/Torque Sensor

The collision detection algorithm of the robot body previously needed to rely on the surface geometry information of the colliding object and no deformation was allowed during the collision process. To solve this problem, a new robot body collision detection algorithm that uses the force information of the six-axis force/torque sensor at the base to self-constrain is proposed which does not rely on the geometric information of the colliding object surface, and the deformation also allows deformation during the collision. In terms of sensor data preprocessing, a gravity and dynamic force compensation algorithm for the six-axis force/torque sensor at the base is proposed to ensure that the reading of the six-axis force/torque sensor at the base always maintains the value of 0 when the robot is working. Then, the robot is considered to have collided with the outside world when the sensor reading exceeds the set threshold. And a precision factor is proposed to analyze the influence of force and collision distance on the accuracy of the algorithm. Finally, the new algorithm proposed in this paper is compared with the traditional algorithm that relies on the geometric information of the colliding body surface. The experimental results indicate that the accuracy of the collision point detection algorithm proposed in this paper is close to that of the traditional method, but it does not need to rely on the geometric information of the collision body surface, and there is no requirement for whether there is deformation during the contact process. It can be concluded that the collision distance is the most important factor affecting the accuracy of the algorithm, followed by the conclusion of the magnitude of the collision force through the calculation of the precision factor. The results show that this method can effectively detect the collision point of the machine body, and the maximum error at the farthest point of the robot is 8.712%, which lays a certain foundation for the subsequent research on human-machine collaboration in small collaborative robots.

Accuracy of Dynamic Force Compensation Varies With Direction and Speed.

This study investigates physical responses to force perturbations while tracking a moving target. The results show accuracy depends on the direction of a force perturbation and speed of the task, but generally not on hand. There are also differences in responses when the force is first applied and when it is removed.

Vertically polarizing undulator with dynamic compensation of magnetic forces

As part of the R program of the LCLS-II project, a novel 3.4-meter-long undulator prototype with horizontal magnetic field and dynamic force compensation has recently been developed at the Advanced Photon Source (APS). Previous steps in this development were the shorter 0.8-meter-long and 2.8-meter-long prototypes. Extensive mechanical and magnetic testing were carried out for each prototype, and each prototype was magnetically tuned using magnetic shims. The resulting performance of the 3.4-meter-long undulator prototype meets all requirements for the LCLS-II insertion device, including limits on the field integrals, phase errors, higher-order magnetic moments, and electron-beam trajectory for all operational gaps, as well as the reproducibility and accuracy of the gap settings.

A parallel alignment device with dynamic force compensation for nanoimprint lithography

Nanoimprint lithography is a nano/micro patterning technology to fabricate functional devices by pressing a template with predefined structures on a substrate. Uniformity of the force distribution between the contacting surfaces should be ensured to produce features with high fidelity. In this paper, a parallel alignment device with the abilities of dynamic force distribution control is developed. By adopting a spherical air bearing held with a 5-degree-of-freedom flexure-based stage, wedge errors between the template and the substrate can be eliminated passively without friction when an imprint force is applied. Since the vertical imprint force is mainly supported by the spherical air bearing, the device is very suitable for high force applications, without causing damage to the delicate compliant stage or precision degradation. Besides, the force distribution of the imprint process is measured, based on which dynamic force compensation is performed by actuating the compliant stage actively. Five-hundred-nm-period grating structures are transferred successfully with the device and proofs effectiveness of the device.

Assistant force compensation for hand movement of patients by using exogenous signals and/or neurophysiological signals

Because functional diseases of the brain can cause disabilities related to human movement control, a compensation method was developed for improving the performance of hand movements. The compensation for human hand movements can be carried out by adding an assistant force that is generated from artificial equipment attached to a human arm. From the experiment on visual target tracking, it was found that the tracking trajectory was adequately represented by a dynamic model of the motion of an articulated industrial robot arm, and the different abilities for movement control among healthy people and patients were classified by different model parameters as position loop gain, velocity loop gain, and response delay. Dynamic force compensation was approached by considering the different control features of the patients. The effectiveness of the proposed compensation method was verified in a simulation study on an actual industrial robot arm. A human-machine interface, e.g., a brain-computer interface (BCI), for realizing the control of artificial equipment to compensate for human hand movements is also presented and discussed.