Compliance Control Research Articles

Optimizing Non-diagonal Stiffness Matrix of Compliance Control for Robotic Assembly Using Deep Reinforcement Learning

With the advent of Industrial 4.0, industrial robots have been widely used in various sectors, e.g., in assembly. Peg-in-hole (PiH) assembly is the most typical one among assembly tasks. In PiH tasks, the robot transfers from a non-contact mode to a contact-rich mode. Instead of switching the position/force control mode with a pause when contact is detected, we deploy a non-diagonal stiffness compliance control for planning the adaptive trajectory to improve the task efficiency and ensure contact safety. In this paper, we proposed a deep reinforcement learning (DRL) method to achieve the above compliance. A compliance controller based on a virtual forward dynamic (FD) model is built. A DRL agent is deployed to optimize the parameters of the non-diagonal stiffness matrix for the built compliance controller to generate a trajectory that adapts to the changing contact condition. The experiment shows the proposed method can control the contact force within a safe range and improve the efficiency of assembly tasks.

Landing control method of a lightweight four-legged landing and walking robot

The prober with an immovable lander and a movable rover is commonly used to explore the Moon’s surface. The rover can complete the detection on relatively flat terrain of the lunar surface well, but its detection efficiency on deep craters and mountains is relatively low due to the difficulties of reaching such places. A lightweight four-legged landing and walking robot called “FLLWR” is designed in this study. It can take off and land repeatedly between any two sites wherever on deep craters, mountains or other challenging landforms that are difficult to reach by direct ground movement. The robot integrates the functions of a lander and a rover, including folding, deploying, repetitive landing, and walking. A landing control method via compliance control is proposed to solve the critical problem of impact energy dissipation to realize buffer landing. Repetitive landing experiments on a five-degree-of-freedom lunar gravity testing platform are performed. Under the landing conditions with a vertical velocity of 2.1 m/s and a loading weight of 140 kg, the torque safety margin is 10.3% and 16.7%, and the height safety margin is 36.4% and 50.1% for the cases with or without an additional horizontal disturbance velocity of 0.4 m/s, respectively. The study provides a novel insight into the next-generation lunar exploration equipment.

EMG-driven shared human-robot compliant control for in-hand object manipulation in hand prostheses

Objective. The limited functionality of hand prostheses remains one of the main reasons behind the lack of its wide adoption by amputees. Indeed, while commercial prostheses can perform a reasonable number of grasps, they are often inadequate for manipulating the object once in hand. This lack of dexterity drastically restricts the utility of prosthetic hands. We aim at investigating a novel shared control strategy that combines autonomous control of forces exerted by a robotic hand with electromyographic (EMG) decoding to perform robust in-hand object manipulation. Approach. We conduct a three-day long longitudinal study with eight healthy subjects controlling a 16-degrees-of-freedom robotic hand to insert objects in boxes of various orientations. EMG decoding from forearm muscles enables subjects to move, proportionally and simultaneously, the fingers of the robotic hand. The desired object rotation is inferred using two EMG electrodes placed on the shoulder that record the activity of muscles responsible for elevation and depression. During the object interaction phase, the autonomous controller stabilizes and rotates the object to achieve the desired pose. In this study, we compare an incremental and a proportional shoulder-decoding method in combination with two state machine interfaces offering different levels of assistance. Main results. Results indicate that robotic assistance reduces the number of failures by and, when combined with an incremental shoulder EMG decoding, leads to faster task completion time (median = 16.9 s), compared to other control conditions. Training to use the assistive device is fast. After one session of practice, all subjects managed to achieve tasks with less failures. Significance. Shared control approaches that give some authority to an autonomous controller on-board the prosthesis are an alternative to control schemes relying on EMG decoding alone. This may improve the dexterity and versatility of robotic prosthetic hands for people with trans-radial amputation. By delegating control of forces to the prosthesis’ on-board control, one speeds up reaction time and improves the precision of force control. Such a shared control mechanism may enable amputees to perform fine insertion tasks solely using their prosthetic hands. This may restore some of the functionality of the disabled arm.

Application of a compliance system to prevent corporate fraud in large companies

The use of compliance systems is one of the most important components of ensuring the functioning of the activities of large companies in conditions of a high level of security. Working with big data puts organizations in front of various problems related to confidentiality and information security. Compliance systems can reduce risks by increasing the competitiveness of enterprises in the market and raising awareness of employees about illegal actions in general. Recently, the application of laws preventing corrupt business transactions has intensified, and the escalating foreign economic situation requires effective actions from business leaders, therefore, the study of ways to apply the compliance system in large companies is necessary. Within the framework of this article, the author examines the essence of compliance, its main functions, as well as methods and methods of compliance control in large organizations operating in the domestic market. An important role in this scientific article is assigned to the levels of development of the compliance system, consideration of international standards, as well as the areas of compliance in large companies, which are highlighted by the author in accordance with the specifics and features of the activities of large companies in the domestic market. The author also considers compliance principles, the observance of which is necessary to ensure the achievement of the company's goals, the development of methods for their adoption, as well as ensuring system control of the functioning of the organization. The paper focused on the need to continue implementing the development strategy of large companies aimed at automating business processes. The main tools for countering corporate fraud that are used by large companies in conditions of aggravation of the risk of corporate fraud are listed.

Assessment of the economic security system of «TransLogistik» LLC

In this article, the author considers the system of economic security of TransLogistics LLC. The article is aimed at analyzing and evaluating the effectiveness of the SES of the specified enterprise. The author notes that enterprises operating in the transport and logistics industry are characterized by the presence of a large set of business processes, which, in turn, increases the number of vulnerabilities and increases the possibility of fraud. The article presents a list of departments responsible for fraud detection within the enterprise in question. Special attention is paid to the issue of information security. According to the author, this is due to the fact that disclosure of information can lead to significant financial and reputational costs. It is noted that the activity of the economic security service is based on the charter of the company and the policy of information security. The author also focuses on the fact that in building a system of economic security, compliance control plays a particularly important role, which establishes the compliance of the activities of an economic entity with acts of the legislative framework. According to the author, the frequency and forms of fraudulent activities largely depend on the organizational structure of the enterprise and ongoing business processes. An analysis of these aspects will make it possible to determine at what stage and by whom a particular offense is committed, as well as to timely implement measures to eliminate them and further prevent them at the identified stages. The author argues that the fraud matrix is a practically useful and effective tool in this case. The article details the meaning of this matrix and the principles of its compilation. The most common form of corporate fraud, according to the author, is partnership actions that do not comply with contractual obligations or concealment by them of true information about their financial situation. The article provides a relevant example and the consequences of this form of fraud. In the final part of the article, the author formulates conclusions regarding the effectiveness of the instrumental apparatus used to combat corporate fraud.

Safety-Aware Hierarchical Passivity-Based Variable Compliance Control for Redundant Manipulators

This article presents a hierarchical passivity-based compliance controller that exploits robot redundancy and aims at achieving an impedance behavior with a time-varying stiffness on all the priority levels. Unfortunately, this gives rise to certain control actions that lead to the loss of the safety-critical passivity feature. To deal with this problem, we employ the concept of virtual <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">energy tanks</i> that keep track of the passivity violating energy in the system, ensuring that it remains bounded. This restores the passivity in the system, which guarantees the stable interaction with any passive environment. Furthermore, we augment our controller with an additional safety layer, which ensures that the energy injected through the tank into the system remains below a safe limit, defined based on the maximum kinetic energy allowed in the system. Finally, our approach is validated in terms of performance during task execution and safety both in simulations and on real-robot hardware.

Active Compliance Control of a Position-Controlled Industrial Robot for Simulating Space Operations

An industrial robot with a six-axis force/torque sensor is usually used to produce a zero-gravity environment for testing space robotic operations. However, using traditional force control methods, such as admittance control, causes position-controlled industrial robots to undergo from force divergence owing to intrinsic time delay. In this paper, a new force control method is proposed to eliminate the force divergence. A hardware-in-the-loop (HIL) simulator with an industrial robot is first presented. The free-floating satellite dynamics and the motion mapping from the satellites to simulator are both established. Thus, the effects of measurement delay and dynamic response delay on contact velocity and force are investigated. After that, a real-time estimation method for contact stiffness and damping is proposed based on the adaptive Kalman filter. The measurement delay is compensated by a phase lead model. Moreover, the identified contact parameters are adopted to modify contact forces, and thus the dynamics response delay can be compensated for. Finally, a co-simulation and experiments were conducted to verify the force control method. The results show that contact stiffness and damping could be identified exactly and that the simulation divergence could be prevented. This paper proposes an active compliance control method that can deal with force constrained tasks of a position-controlled robot in unknown environments.

Coordinated Compliance Control Method of Five-Axis Redundant Industrial Manipulator Based on Monocular Vision

In order to improve the accuracy of the five-axis redundant industrial robot arm in grasping static objects and shorten the grasping time, a coordinated compliance control method based on a monocular vision for the five-axis redundant industrial robot arm is proposed in this paper. Using the monocular vision ranging method, the three-dimensional coordinates of the target object in a base coordinate system of the five-axis redundant industrial robotic arm are calculated and object target positioning is achieved. According to the acquired object target position, the traditional Euler angle is used to calculate the actuator posture impedance at the end of the robotic arm, thereby realizing the coordinated compliant control of the five-axis redundant industrial manipulator. The simulation experiment results show that the proposed coordinated compliance control method for a five-axis redundant industrial manipulator based on monocular vision can successfully grasp the target object in the shortest time and has high practical value.

Dataset with Tactile and Kinesthetic Information from a Human Forearm and Its Application to Deep Learning.

There are physical Human-Robot Interaction (pHRI) applications where the robot has to grab the human body, such as rescue or assistive robotics. Being able to precisely estimate the grasping location when grabbing a human limb is crucial to perform a safe manipulation of the human. Computer vision methods provide pre-grasp information with strong constraints imposed by the field environments. Force-based compliant control, after grasping, limits the amount of applied strength. On the other hand, valuable tactile and proprioceptive information can be obtained from the pHRI gripper, which can be used to better know the features of the human and the contact state between the human and the robot. This paper presents a novel dataset of tactile and kinesthetic data obtained from a robot gripper that grabs a human forearm. The dataset is collected with a three-fingered gripper with two underactuated fingers and a fixed finger with a high-resolution tactile sensor. A palpation procedure is performed to record the shape of the forearm and to recognize the bones and muscles in different sections. Moreover, an application for the use of the database is included. In particular, a fusion approach is used to estimate the actual grasped forearm section using both kinesthetic and tactile information on a regression deep-learning neural network. First, tactile and kinesthetic data are trained separately with Long Short-Term Memory (LSTM) neural networks, considering the data are sequential. Then, the outputs are fed to a Fusion neural network to enhance the estimation. The experiments conducted show good results in training both sources separately, with superior performance when the fusion approach is considered.

Compliant Control of Lower Limb Rehabilitation Exoskeleton Robot Based on Flexible Transmission

Compliant Control of Lower Limb Rehabilitation Exoskeleton Robot Based on Flexible Transmission

Robotic Peg-in-Hole Assembly Strategy Research Based on Reinforcement Learning Algorithm

To improve the robotic assembly effects in unstructured environments, a reinforcement learning (RL) algorithm is introduced to realize a variable admittance control. In this article, the mechanisms of a peg-in-hole assembly task and admittance model are first analyzed to guide the control strategy and experimental parameters design. Then, the admittance parameter identification process is defined as the Markov decision process (MDP) problem and solved with the RL algorithm. Furthermore, a fuzzy reward system is established to evaluate the action–state value to solve the complex reward establishment problem, where the fuzzy reward includes a process reward and a failure punishment. Finally, four sets of experiments are carried out, including assembly experiments based on the position control, fuzzy control, and RL algorithm. The necessity of compliance control is demonstrated in the first experiment. The advantages of the proposed algorithms are validated by comparing them with different experimental results. Moreover, the generalization ability of the RL algorithm is tested in the last two experiments. The results indicate that the proposed RL algorithm effectively improves the robotic compliance assembly ability.

SEMG-Based Gain-Tuned Compliance Control for the Lower Limb Rehabilitation Robot during Passive Training.

The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems of insufficient physiological information and unsatisfactory safety performance in the compliance control strategy for the lower limb rehabilitation robot during passive training, this study developed a surface electromyography-based gain-tuned compliance control (EGCC) strategy for the lower limb rehabilitation robot. First, the mapping function relationship between the normalized surface electromyography (sEMG) signal and the gain parameter was established and an overall EGCC strategy proposed. Next, the EGCC strategy without sEMG information was simulated and analyzed. The effects of the impedance control parameters on the position correction amount were studied, and the change rules of the robot end trajectory, man-machine contact force, and position correction amount analyzed in different training modes. Then, the sEMG signal acquisition and feature analysis of target muscle groups under different training modes were carried out. Finally, based on the lower limb rehabilitation robot control system, the influence of normalized sEMG threshold on the robot end trajectory and gain parameters under different training modes was experimentally studied. The simulation and experimental results show that the adoption of the EGCC strategy can significantly enhance the compliance of the robot end-effector by detecting the sEMG signal and improve the safety of the robot in different training modes, indicating the EGCC strategy has good application prospects in the rehabilitation robot field.

Bayesian optimization with unknown constraints in graphical skill models for compliant manipulation tasks using an industrial robot.

This article focuses on learning manipulation skills from episodic reinforcement learning (RL) in unknown environments using industrial robot platforms. These platforms usually do not provide the required compliant control modalities to cope with unknown environments, e.g., force-sensitive contact tooling. This requires designing a suitable controller, while also providing the ability of adapting the controller parameters from collected evidence online. Thus, this work extends existing work on meta-learning for graphical skill-formalisms. First, we outline how a hybrid force–velocity controller can be applied to an industrial robot in order to design a graphical skill-formalism. This skill-formalism incorporates available task knowledge and allows for online episodic RL. In contrast to the existing work, we further propose to extend this skill-formalism by estimating the success probability of the task to be learned by means of factor graphs. This method allows assigning samples to individual factors, i.e., Gaussian processes (GPs) more efficiently and thus allows improving the learning performance, especially at early stages, where successful samples are usually only drawn in a sparse manner. Finally, we propose suitable constraint GP models and acquisition functions to obtain new samples in order to optimize the information gain, while also accounting for the success probability of the task. We outline a specific application example on the task of inserting the tip of a screwdriver into a screwhead with an industrial robot and evaluate our proposed extension against the state-of-the-art methods. The collected data outline that our method allows artificial agents to obtain feasible samples faster than existing approaches, while achieving a smaller regret value. This highlights the potential of our proposed work for future robotic applications.

Design optimization of a linkage-based 2-DOF wheel mechanism for stable step climbing

This paper presents the design optimization of a linkage-based wheel mechanism with two degrees of freedom, for stable step climbing. The mechanism has seven rotational joints and one prismatic joint. Kinematic and dynamic analyses of the mechanism were performed. The design was optimized in terms of linkage length and architecture to better manipulate the mechanism in its workspace, which was defined here by the targeted step size, as well as to ensure stability while climbing stairs. Optimization by genetic algorithm was performed using MATLAB. The optimized mechanism exhibited enhanced torque transmission from the input torque to the exerted for at the lobe of the wheel. Compliance control of the transformation will be addressed in the future.

ВИЗНАЧЕННЯ ВАРТОСТІ ПОСЛУГ З ТЕХНІЧНОГО НАГЛЯДУ НА АВТОМОБІЛЬНИХ ДОРОГАХ ЗАГАЛЬНОГО КОРИСТУВАННЯ НА ВСІХ ЕТАПАХ ІНВЕСТИЦІЙНОГО ПРОЦЕСУ

Introduction. The process of new construction, reconstruction and overhaul of the roads requires the contractor to comply with all norms and rules established by regulatory documents and the customer of the works. Such functions are entrusted to the customer, or they can be performed by specialists who are engaged to perform technical supervision at the road works facilities. Technical supervision specialists primarily monitor the process of work at the facility, the measures of which provide for the implementation of a complex of actions to check the quality of work and protect the interests of the customer. Problem Statement. Consideration of this subject is the need to reliably determine the amount of funds for technical supervision of road construction facilities at all stages of the investment process. After all, the performance of technical supervision services includes the involvement of the needed number of specialists and the determination of their functional duties at the facility. The correct determination of the required amount of funds depends of that, who exactly will perform technical supervision works and is important as from the point of view of the customers of road works and services, and from the point of view of the needs of the enterprises themselves, if they are involved in the performance of technical supervision works. Purpose. Given the need for technical supervision and compliance control of all works on the road construction facilities throughout the entire period of their execution, there is a need for a methodology for determining the cost of technical supervision services at the road works facilities when preparing the investor estimate documents, forming contract prices and mutual settlements. Materials and methods. The calculation of costs for the provision of technical supervision services is performed taking into account the stage of road works, the duration of works at the facility, the complexity of these works, and the required number of technical supervision specialists. Results. The article highlights the practical meaning of the term «technical supervision», the conditions that affect the determination of the amount of funds for the implementation of technical supervision, the rules for calculation of technical supervision services cost at all stages of the investment process, and the approximate structure of their cost. Conclusions. Taking into account technical supervision services by the customer at the stage of preparing the investor estimate documentation will allow reducing the costs of road works in the future. The work of technical supervision specialists will contribute to the high-quality implementation of road works by monitoring the contractor’s compliance with project decisions, the scope of works and the quality of materials control. That is why it is needed to calculate correctly the technical supervision services cost, consider the real structure of these costs and the conditions of construction of facilities.

Intelligent Interactive Control via Haptic E‐skin for Human–Robot Interaction and Collaboration

Human–robot interaction and collaboration are emerging as critical and necessary technologies as robots become more commonplace in our lives. Haptic perception and intelligent control are essential to ensure safe and dexterous interactions between humans and robots. Traditional interaction methods using robot proprioceptors rely on robot dynamic models that complicate robotic controls and narrow their adaptabilities. Herein, an intelligent interactive control method is proposed based on a generalized virtual spring‐damping force‐touch mechanism using haptic e‐skin, which converts contact forces and contact positions on the e‐skin to generalized forces for implementing robot compliance controls of multidimensional movements. By touching the e‐skin mounted on a robot arm, a human can readily manipulate the robot arm, achieving flexible movement and rotation. An intelligent architecture of human–robot‐in‐the‐loop is proposed to accomplish versatile interactive and collaborative actions. A task learning is demonstrated for a robot from human, that is, a human teaches a robot how to pick up, carry, and place an object into a box by hand‐by‐hand teaching, which shows promising prospects in intelligent robot applications.

Resistant Compliance Control for Biped Robot Inspired by Humanlike Behavior

Compliance control is important for the realization of disturbance absorption in biped robots. However, under a sustained disturbance, compliance control causes the robot’s balance to deteriorate because of its floating base nature. Humans address this problem by resisting external disturbance. When pushed, a human will reconcile their posture with the applied external force and then push back to maintain balance. Inspired by this behavior, we propose a compliance control strategy for biped robots called resistant compliance, which allows a robot to comply with the external disturbance initially and then repel the disturbance to reduce the imbalance caused by the reconciliatory motion. As a result, the robot can obtain improved environment-interaction stability and react more like a typical human, thus making both its locomotion and its interactions more stable and safer. To realize this control strategy, the virtual-mass-model (VMM) control is redesigned to unify the disturbances from unexpected external forces and an inclined floor. Then, the VMM control is combined with the linear-inverted-pendulum model to realize resistant compliant motion. Model predictive control is used to track the reference zero-moment-point trajectory, which is essential for locomotion. To validate the proposed control strategy, the method is implemented on the human-sized humanoid robot BHR-T.

Goodness of fit in the Chinese context of socialization in the first three years.

Based on the goodness-of-fit theory, the current research examined how parental socialization expectations and socialization practices in infancy predicted child social adjustment in the preschool year dependent on child characteristics in toddlerhood with a longitudinal sample of Chinese families. Participants were 272 Chinese mother-child dyads. Maternal socialization goals of child autonomy and obedience were assessed when the child was 6 months old. Maternal respect for autonomy and negative control were observed in free-plays at 15 months. Mothers reported child compliance and inhibitory control at 25 months and rated child externalizing behaviors at 37 months. Results showed that for children with low levels of compliance or high levels of inhibitory control, obedience socialization goals predicted more externalizing behaviors, whereas for children with high levels of compliance or low levels of inhibitory control, obedience socialization goals predicted fewer externalizing behaviors. Moreover, for children with high levels of inhibitory control, higher levels of respect for autonomy or lower levels of negative control foretold fewer externalizing behaviors. Conversely, for children with low levels of inhibitory control, lower levels of respect for autonomy or higher levels of negative control forecasted fewer externalizing behaviors. Together, our findings demonstrate that socialization expectations, socialization practices, and child characteristics are jointly predictive of social adjustment across early childhood and all the significant interactions are characterized by the pattern of a contrastive effect, therefore congruently supporting the goodness-of-fit hypotheses. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Safety Compliant Control for Robotic Manipulator With Task and Input Constraints

Increasingly, robots are working in close proximity with humans, and in dynamically changing environments. We present a new control architecture that guarantees safety under such conditions, while simultaneously ensuring that task goals are satisfied. Our approach combines Control Barrier Functions (to provide safety guarantees) with Rapidly Exponentially Stabilizing Control Lyapunov functions (to satisfy task constraints and ensure exponential convergence). We formulate the problem completely in the operational space, using super ellipsoids to define safe sets which are dynamically adapted to restrict the robot’s operational space in response to moving obstacles (including humans). Control barrier functions, which can be implemented in real time using quadratic programming, ensure the forward invariance of these safe sets, while minimally perturbing prescribed control trajectories. We demonstrate our approach on a seven degree-of-freedom Kuka LBR iiwa robotic manipulator, both in a physics engine-based simulation and with real hardware experiments.

Easy-to-Deploy Combined Nasal/Throat Swab Robot With Sampling Dexterity and Resistance to External Interference

Robots have been used extensively in the battle against the COVID-19 pandemic since its outbreak. One prominent direction is the use of robots for swab sampling, which not only solves the shortage of medical staffs, but also prevents them from being infected during face-to-face sampling. However, a massive deployment of sampling robots is still not achievable due to their high costs, safety concerns, deployment complexity, and so on. In this letter, we propose a flexible, safe, and easy-to-deploy swab robot in a compact bench-top system. The robot can perform nasal/throat swab sampling tasks as dexterous as a human manual operation. The bio-mimetic rigid interior and soft exterior design guarantee the sampling robot with both flexibility and safety. Furthermore, the integration of 3-D fiber Bragg grating (FBG) based shape sensor and multi-axis force sensor may enhance the control performance. A dedicated constrained compliance control (CCC) algorithm was developed to tackle the unexpected interactions during sampling, which ensures the validity and safety of the sampling under disturbance. Various experiments are conducted to validate our system and prove its feasibility, flexibility, high safety, and efficiency for both nasal/throat swab sampling tasks. The proposed system is promising to be massive duplicated for robotic swab sampling.