Regulation Of Contact Force Research Articles

Enhanced Tracking in Legged Robots through Model Reduction and Hybrid Control Techniques: Addressing Disturbances, Delays, and Saturation

This study introduces a reduced-order leg dynamic model to simplify the controller design and enhance robustness. The proposed multi-loop control scheme tackles tracking control issues in legged robots, including joint angle and contact-force regulation, disturbance suppression, measurement delay, and motor saturation avoidance. Firstly, model predictive control (MPC) and sliding mode control (SMC) schemes are developed using a simplified model, and their stability is analyzed using the Lyapunov method. Numerical simulations under two disturbances validate the superior tracking performance of the SMC scheme. Secondly, an Nth-order linear active disturbance rejection control (LADRC) is designed based on a simplified model and optimization problems. The second-order LADRC-SMC scheme reduces the contact-force control error in the SMC scheme by ten times. Finally, a fourth-order LADRC-SMC with a Smith Predictor (LADRC-SMC-SP) scheme is formulated, employing each loop controller independently. This scheme simplifies the design and enhances performance. Compared to numerical simulations of the above and existing schemes, the LADRC-SMC-SP scheme eliminates delay oscillations, shortens convergence time, and demonstrates fast force-position tracking responses, minimal overshoot, and strong disturbance rejection. The peak contact-force error in the LADRC-SMC-SP scheme was ten times smaller than that in the LADRC-SMC scheme. The integral square error (ISE) values for the tracking errors of joint angles θ1 and θ2, and contact force f, are 1.6636×10−28 rad2⋅s, 1.7983×10−28 rad2⋅s, and 1.8062×10−30 N2⋅s, respectively. These significant improvements in control performance address the challenges in single-leg dynamic systems, effectively handling disturbances, delays, and motor saturation.

A multi-channel photoplethysmography array with contact-force regulation for tonoarteriographic imaging

Aim: Photoplethysmography (PPG) has gained widespread popularity as a non-invasive method for potential cuff-less blood pressure (BP) measurement in smart devices. However, the accuracy of PPG-based devices is often hindered by motion artifacts, site variability, and inconsistent contact force (CF). This study aims to investigate the influence of CF variations on PPG signals. Methods: To address these challenges, we present a novel approach involving a multi-channel PPG array integrated with CF regulation in the form of a wearable wristband. This platform enables the visualization of regional PPG/BP distribution while simultaneously monitoring CF. Moreover, our research explored the relationship between PPG waveform characteristics and CF during wrist extension. Results: The results of this study reveal that the PPG amplitude (PPGA) and the b/a ratios, computed from the second derivative peaks of the PPG AC pulse wave, exhibit inconsistency in reaction to CF variations. Notably, a shape correlation coefficient of 0.65069 between normalized PPG and flipped CF sheds light on how changes in posture affect PPG measurements. Conclusions: The proposed platform shows promise in mitigating the effects of CF and spatial positioning on PPG, thereby improving measurement precision and offering a novel approach to image tonoarteriographic (TAG) activities for continuous hypertension management.

Contact force regulation in physical human-machine interaction based on model predictive control

AbstractWith increasing attention to physical human-machine interaction (pHMI), new control methods involving contact force regulation in collaborative and coexistence scenarios have spread in recent years. Thanks to its internal robustness, high dynamic performance, and capabilities to avoid constraint violations, a Model Predictive Control (MPC) action can pose a viable solution to manage the uncertainties involved in those applications. This paper uses an MPC-driven control method that aims to apply a well-defined and tunable force impulse on a human subject. After describing a general control design suitable to achieve this goal, a practical implementation of such a logic, based on an MPC controller, is shown. In particular, the physical interaction considered is the one occurring between the body of a patient and an external perturbation device in a dynamic posturography trial. The device prototype is presented in both its hardware architecture and software design. The MPC-based main control parameters are thus tuned inside hardware-in-the-loop and human-in-the-loop environments to get optimal behaviors. Finally, the device performance is analyzed to assess the MPC algorithm’s accuracy, repeatability, flexibility, and robustness concerning the several uncertainties due to the specific pHMI environment considered.

Interaction Control of a Robotic Manipulator With the Surface of Deformable Object

Robotic manipulation of deformable objects has drawn the attention of researchers over the past few years and is associated with a large spectrum of new application perspectives. In this article, we present an efficient integrated motion planning framework to effectively and accurately control a robotic manipulator executing interactive tasks on the surface of a deformable object. The proposed interactive motion planning framework is based on a mesh representation of the object, integrating three efficient preprocessing algorithmic steps, including visual object segmentation, finite element method deformation tracking, and local mesh parameterization. The use of barycentric coordinates, defined on the mesh triangles, enables the establishment of bijective transformations between the deformable part of an object surface and its planar (static and dynamic) parameterized mapping. By merging these spatial transformations with the preprocessing steps, in combination with an active stiffness scheme for robot manipulator control, we are able to achieve accurate and reactive motion planning of interactive trajectories, even under large and persistent visual occlusions (such as due to the presence of the robot in the visual scene). An extensive experimental evaluation study is presented, involving a robotic manipulator in interaction with a hemispherical model of controllable periodic active deformation, which permits precise ground truth derivation. Motion planning accuracy is evaluated in comparison with our previous direct vision-based approach, showing clearly superior performance of the proposed approach under all experimental conditions. The performance of the proposed framework is also further highlighted in tasks involving physical point tracking, interactive programming by human demonstration, as well as contact force regulation.

A Hierarchical Compliance-Based Contextual Policy Search for Robotic Manipulation Tasks With Multiple Objectives

Contextual policy search methods have demonstrated the potential to acquire robotic skill generalization on trajectory-shaping-based tasks. However, it is still challenging for robotic contact-rich manipulation tasks because contact force regulation, reference trajectory adaptation, and task generalization must be fulfilled simultaneously. To this end, a hierarchical compliance-based contextual policy search (HC-CPS) approach is proposed to learn the robotic compliant skills for force, motion, and task adaptation. Specifically, the parameterized impedance-conditioned action space is proposed for reinforcement learning lower-level policy to obtain the compliance for reference motion regulation and contact force control, while a linear Gaussian contextual policy is formulated as the higher-level policy to optimize the context-conditioned impedance parameters for task generalization; therefore, a family of contact-rich manipulation tasks with multiple objectives is achieved. Moreover, data efficiency is further improved by two aspects: first, a variation encoder-decoder model is proposed to estimate the underlying constraints of impedance parameters over the actions, leading to the mitigated extrapolation error for lower-level policy off-policy learning; second, a composite forward model is proposed to generate artificial trajectories and reduce the reward bias for higher-level contextual policy learning. The HC-CPS approach is validated by three simulated manipulation tasks and the real-world dual peg-in-hole assembly tasks with two kinds of objectives, and the results demonstrate the effectiveness of HC-CPS.

Pantograph Catenary Contact Force Regulation Based on Modified Takagi-Sugeno Fuzzy Models

In this paper, a new contact force control technique, based on the modified Takagi-Sugeno model and the parallel distributed compensation concept is developed to suppress vibrations between the pantograph and the catenary by regulating the contact force to a reference value, thereby achieving stable current collection. The proposed method uses simple and standard PID and modified Takagi-Sugeno fuzzy controllers. The two controllers guarantee the designed system's robust stability. Furthermore, based on a simplified pantograph–catenary system model, the comparative simulation results show that variations of the contact force can be almost attenuated. As a result, the system stability is guaranteed, and the performance robustness is verified.

Disturbance Observer-Based Sliding Mode Controller for Regulating Pantograph–Catenary Contact Force

For most electrified railways, pantographs play a vital role in transmitting energy from overhead line to vehicles, and therefore a stable and continuous contact behavior is required. This paper proposes a disturbance observer-based sliding mode controller (DO-SMC) for the problem of pantograph–catenary contact force regulation. The simulation results show that the DO-SMC with a chattering alleviation approach can effectively reduce contact force fluctuation through a reasonable control input.

Boxcar Averaging Scanning Nonlinear Dielectric Microscopy.

Scanning nonlinear dielectric microscopy (SNDM) is a near-field microwave-based scanning probe microscopy method with a wide variety of applications, especially in the fields of dielectrics and semiconductors. This microscopy method has often been combined with contact-mode atomic force microscopy (AFM) for simultaneous topography imaging and contact force regulation. The combination SNDM with intermittent contact AFM is also beneficial for imaging a sample prone to damage and using a sharp microscopy tip for improving spatial resolution. However, SNDM with intermittent contact AFM can suffer from a lower signal-to-noise (S/N) ratio than that with contact-mode AFM because of the shorter contact time for a given measurement time. In order to improve the S/N ratio, we apply boxcar averaging based signal acquisition suitable for SNDM with intermittent contact AFM. We develop a theory for the S/N ratio of SNDM and experimentally demonstrate the enhancement of the S/N ratio in SNDM combined with peak-force tapping (a trademark of Bruker) AFM. In addition, we apply the proposed method to the carrier concentration distribution imaging of atomically thin van der Waals semiconductors. The proposed method clearly visualizes an anomalous electron doping effect on few-layer Nb-doped MoS2. The proposed method is also applicable to other scanning near-field microwave microscopes combined with peak-force tapping AFM such as scanning microwave impedance microscopy. Our results indicate the possibility of simultaneous nanoscale topographic, electrical, and mechanical imaging even on delicate samples.

Intelligent Contact Force Regulation of Pantograph–Catenary Based on Novel Type-Reduction Technology

In this paper, an intelligent control scheme is proposed to suppress vibrations between the pantograph and the catenary by regulating the contact force to a reference value, thereby achieving stable current collection. In order to reduce the computational cost, an interval Type-2 adaptive fuzzy logic control with the Moradi–Zirhohi–Lin type reduction method is applied to deal with model uncertainties and exterior interference. Based on a simplified pantograph–catenary system model, the comparative simulation results show that variation of the contact force can be attenuated and variation disturbances can be repressed simultaneously. Furthermore, in terms of computational burden, the proposed type reduction method outperforms other type reduction methods.

Design of a Pose and Force Controller for a Robotized Ultrasonic Probe Based on Neural Networks and Stochastic Gradient Approximation

In medicine and engineering, the implementation of a diagnostic test using an ultrasonic sensor requires suitable contact conditions, and a correct pose to attain the best signal transmission settings. A soft sensor probe provides a good surface adaptation and forces transfer, but it introduces nonlinearities and noisy measurements, making it difficult to control the probe during a real time test by conventional algorithms. In this work, a data driven controller is developed to control force and pose of a soft contact ultrasound sensor. The adaptive controller is based on a fuzzy-rules emulated network structure with the learning algorithm using a stochastic gradient approximation. The proposed control algorithm overcomes the noise environment conditions and nonlinearities of the unknown nonlinear discrete-time system. This was numerically validated and then, experimentally tested with an industrial robotic system using an ultrasonic probe designed in our lab. The results show that the proposed controller performs well under the contact-force regulation and can find the correct contact orientation with a fast convergence.

Prediction Control for Brachytherapy Robotic System

In contemporary brachytherapy procedure, needle placement at desired location is challenging due to a variety of reasons. We have designed and fabricated an image-guided robot-assisted brachytherapy system to improve the needle placement and seed delivery. In this article we have used two different predictive control strategies in order to investigate the needle insertion efficacy and system dynamics during prostate brachytherapy. First, we used neural network predictive control (NNPC) to predict an insertion force. The NNPC uses the linearized state-space model of the robotic system to predict future system performances. Second, we used feedforward model predictive control (MPC) which allows the controller to compensate the influence of a measured disturbance's impact immediately rather than waiting until the effect appears in the system. Feedback control problem for the contact force regulation is considered. The simulation results and experiments for both cases are presented and compared.

Contact force regulation in wire-actuated pantographs via variable structure control and frequency-domain techniques

One of the main problems in high-speed-train transportation systems is related to the current collection quality, that can dramatically decrease because of oscillations of the pantograph-catenary system. This problem has been addressed by means of active pantographs. In this paper we present some results about the possible implementation of variable structure control (VSC) techniques on a wire actuated symmetric pantograph. Such an actuator was suggested in the literature as a viable solution to building an active pantograph by modifying a passive pantograph currently used by Italian Railways. The use of VSC with sliding modes was considered in order to cope with the system uncertainties due to the overhead suspended catenary. Recent results about the frequency-based analysis of VSC systems featuring second-order sliding modes are exploited to avoid the performance-destroying effect of the resonant wire actuator and to get a continuous control force without using observers. We show by simulations that the contact force results are very close to the desired set-point also in the presence of measurement noise.

Force Tracking Impedance Control with Variable Target Stiffness

In this paper, a novel force tracking impedance control strategy is presented in which target stiffness is varied on-line to regulate the desired contact force without any knowledge of the environment. Humans can control contact force by adjusting their arm stiffness. The contact force can be either increased by making one's arm stiffer or decreased by reducing the arm stiffness. Furthermore, humans can keep the force tracking error within a certain range without any knowledge of environmental parameters as long as how much force they exert on the object is known to them. Analogously, the proposed control scheme achieves a contact force regulation control by adjusting the target stiffness of the impedance control. The new force tracking impedance control scheme does not require estimating environment stiffness or locations since the controller is adapted only based on the previous force tracking error between the desired and real contact force. Stability of the proposed scheme is discussed with a quadratic Lyapunov function. Extensive simulation studies with a 7 degree of freedom (DoF) robot manipulator using full arm dynamics are conducted to demonstrate the validity of the proposed scheme.

Multidigit Control of Contact Forces During Transport of Handheld Objects

When an object is lifted vertically, the normal force increases and decreases in tandem with tangential (load) force to safely avoid slips. For horizontal object transport, horizontal forces at the contact surfaces can be decomposed into manipulation forces (producing acceleration/deceleration) and grasping forces. Although the grasping forces must satisfy equilibrium constraints, it is not clear what determines their modulation across time, nor the extent to which they result from active muscle contraction or mechanical interactions of the digits with the moving object. Grasping force was found to increase in an experimental condition where the center of mass was below the contact plane, compared with when it was in the contact plane. This increase may be aimed at stabilizing object orientation during translation. In another experimental condition, more complex moments were introduced by allowing the low center of mass to swing around a pivot point. Electromyographic (EMG) activity recorded from several intrinsic and extrinsic hand muscles failed to reveal active feedback regulation of contact force in this situation. Instead, in all experimental conditions, EMG data revealed a strategy of feedforward stiffness modulation. Multiple regression analysis revealed that muscle activity at remote digits (e.g., the index and ring fingers) was highly correlated with the contact force measured at another digit (e.g., the thumb). The data suggest that to maintain grasp stability during horizontal translation, predictable as well as somewhat unpredictable inertial forces are compensated for by controlling the stiffness of the hand through cocontraction and modulation of hand muscle activity.

A method for controlling robotic contact tasks

SUMMARYIn robotic tasks where the manipulator has to make transition from free space motion to constrained one, there always exists a inevitable impact phase (contact transition phase). Examples can be the autonomous exploratory motion of the end-effector in a cluttered environment, or grasping and manipulation of objects using dexterous mechanical end-effector. A number of controllers have been proposed in the literature with various discussions on their practical implications. In this paper a simple and efficient controller is proposed for the robotic contact tasks. The controller is based on the notion of switching control law where the structure of the controller remains unchanged during the phase transition and only the magnitudes of its gains are changed. The proposed control law maintans the stable performance during the impact phase of the manipulator when making contact with general environment. In addition, the controller exhibits stable and robust performance during the post-contact phase with the desired contact force regulation. The stability of the proposed controller is shown using the Lyapunov method which guarantees the exponential rate of convergence of the state during the contact transition to post-contact phase. Experimental results are presented to demonstrate the practicality of the proposed controller.