Admittance Control Research Articles

Optimization of percutaneous intervention robotic system for skin insertion force.

Percutaneous puncture is a common interventional procedure, and its effectiveness is influenced by the insertion force of the needle. To optimize outcomes, we focus on reducing the peak force of the needle in the skin, aiming to apply this method to other tissue layers. We developed a clinical puncture system, setting and measuring various variables. We analyzed their effects, introduced admittance control, set thresholds, and adjusted parameters. Finally, we validated these methods to ensure their effectiveness. Our system meets application requirements. We assessed the impact of various variables on peak force and validated the effectiveness of the new method. Results show a reduction of about 50% in peak force compared to the maximum force condition and about 13% compared to the minimum force condition. Finally, we summarized the factors to consider when applying this method. To achieve peak force suppression, initial puncture variables should be set based on the trends in variable impact. Additionally, the factors of the new method should be introduced using these initial settings. When selecting these factors, the characteristics of the new method must also be considered. This process will help to better optimize peak puncture force.

Teleoperation in robot-assisted MIS with adaptive RCM via admittance control

AbstractThis paper presents the development and assessment of a teleoperation framework for robot-assisted minimally invasive surgery (MIS). The framework leverages our novel integration of a previously developed adaptive remote center of motion (RCM) using admittance control. This framework operates within a redundancy resolution method specifically designed for the RCM constraint. We introduce a compact, low-cost, and modular custom-designed instrument module (IM) that ensures integration with the manipulator, featuring a force/torque sensor, a surgical instrument, and an actuation unit for driving the surgical instrument. The paper details the complete teleoperation framework, including the telemanipulation trajectory mapping, kinematic modelling, control strategy, and the integrated admittance controller. Finally, the system’s capability to perform various surgical tasks was demonstrated, including passing a thread through the rings, picking and placing objects, and trajectory tracking.

Variable Admittance Control of High Compatibility Exoskeleton Based on Human–Robotic Interaction Force

The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Approximation-Based Admittance Control of Robot-Environment Interaction With Guaranteed Performance

Approximation-Based Admittance Control of Robot-Environment Interaction With Guaranteed Performance

Torque-Bounded Admittance Control With Implicit Euler Realization of Set-Valued Operators

Torque-Bounded Admittance Control With Implicit Euler Realization of Set-Valued Operators

Through-Window Home Aerial Delivery System with In-Flight Parcel Load and Handover: Design and Validation in Indoor Scenario

Abstract This paper presents the design, development, and validation in indoor scenario of an aerial delivery system intended to conduct the delivery of light parcels directly to the user through the window of his/her home, motivated by the convenience of facilitating the access to medicines to people with reduced mobility.The system consists of a fully-actuated multi-rotor (FAMR) equipped with a front basket where the parcel to be delivered is loaded by a lightweight and compliant anthropomorphic dual arm system (LiCAS) located at the supply point, using one of the arms to drop the parcel in the basket while the other arm holds its base to support the sudden moment exerted at the FAMR. The paper analyses four types of physical interactions raised during the operation on flight: (1) sudden changes in the mass distribution of the FAMR during the load/unload phase, affecting the multi-rotor position-attitude controllers, (2) impact and impulsive forces exerted by the human on the FAMR to demonstrate the reliability and robustness of conventional cascade controllers, (3) passive accommodation of the LiCAS while holding the FAMR during the parcel load, relying on the mechanical joint compliance, and (4) compliant human–FAMR interaction, interpreting the multi-rotor pose control error as a Cartesian/angular deflection to implement an admittance controller that allows the user guiding the platform. Experimental results allow the identification and characterization of these effects for different payload masses. The execution of the complete operation, involving the parcel load with the LiCAS and handover by the user through a window, is validated in a representative indoor scenario. Graphical Abstract

Finite-time SMC-based admittance controller design of macro-micro robotic system for complex surface polishing operations

In the field of robotic polishing, achieving uniform material removal typically involves addressing the issue of constant contact force control. However, multi-source external disturbances in the polishing scenarios of complex workpiece surfaces can severely affect the robot’s force control accuracy. To enhance the responsiveness and disturbance rejection capabilities of robots in the compliant polishing process, this paper proposes an adaptive admittance controller with practical finite-time stability. A virtual control input is introduced into the basic admittance control framework in light of the state space theory, aiming to provide flexibility for common adaptive law designs. On this basis, a robust sliding mode control (SMC) algorithm is proposed to suppress external disturbances. The force tracking error is theoretically proven to achieve finite-time convergence when applying the proposed control strategy. Experimental results across various polishing scenarios demonstrate that, compared with the existing admittance control strategies, the proposed method can reduce fluctuations of the polishing force and improve the surface quality, thus verifying its effectiveness.

Human-redundant robot interaction and redundancy utilization based on three-dimensional force sensor

To make full use of redundant characteristics, the inverse kinematics algorithm based on augmented Jacobian matrix with the goal of avoiding joint limit and obstacle is adopted. Then, admittance control system is established for human-robot interaction, and force control is converted into motion control of robot. Through the expansion of Jacobian matrix, the model of joint limit avoidance is established. Regarding obstacle avoidance in human-robot interaction process, the potential function gradient is calculated and augmented Jacobian matrix is formed. Thus, comprehensive control model of human-robot interaction and obstacle avoidance is established. When the external force is applied, the robot can move smoothly along the human hand. The robot's motion process is smooth and compliant. At the same time, when performing task of avoiding joint limit, the values of the joint angle are within the set range. The average angle margin of the four joints is over 60 %. So the goal of avoiding the joint limit is achieved. When adding obstacle avoidance in the interaction control, the difference value between the minimum distance and safe distance is always positive. The safety margin of the distance is over 20 %. So the robot does not contact with the obstacle. So human-robot interaction and redundancy utilization can be realized simultaneously.

Adaptive optimal concurrent control for detumbling space non-cooperative target via multipoint repeated contact

Space debris generally exhibits complex tumbling motions, and its direct capture may cause damage to space manipulator and base spacecraft. Current detumbling strategies typically require continuous contact collisions with the target and do not take into account actuator limitations. Thus, this paper presents an adaptive optimal concurrent control of space free-floating multi-fingered robot (SFMR) for multipoint repeated contact detumbling of non-cooperative targets. Firstly, the multipoint repeated intermittent contact model between the SFMR and the target is established. Further, an optimal admittance control that considers manipulator actuator limits and target motion bounds is formulated to generate a compliant detumbling trajectory. Through transforming the state and input inequality constraints into extended dynamical subsystems and saturation functions, respectively, the optimal control problem (OCP) is transformed into a readily solvable equality constraint problem. Moreover, an enhanced nonsingular terminal sliding mode (ENTSM) control with radial basis function neural network (RBFNN) compensation is presented in the presence of lumped uncertainties and external disturbances, which achieves rapid finite-time convergence and low-chattering. The simulation results show that the proposed method can reduce the velocity of the space target effectively without causing base spacecraft interference while achieving accurate trajectory tracking.

Design and Research of the Grasping Force Feedback Mechanism of Flexible Surgical Robots.

Robot-assisted microsurgery (RAMS) is gradually becoming the preferred method for some delicate surgical procedures. However, the lack of haptic feedback reduces the safety of the surgery. Surgeons are unable to feel the grasping force between surgical instruments and the patient's tissues, which can easily lead to grasping failure or tissue damage. This paper proposes a tendon-driven grasping force feedback mechanism, consisting of a follower hand and a leader hand, to address the lack of grasping force feedback in flexible surgical robots. Considering the friction in the tendon transmission process, a grasping force estimation model is established for the follower hand. The admittance control model is designed for force/position control of the leader hand. Through experimental validation, it has been confirmed that the grasping force sensing range of the follower hand is 0.5-5N, with a sensing accuracy of 0.3N. The leader hand is capable of providing feedback forces in the range of 0-5N, with a static force accuracy of 0.1N. The designed mechanism and control strategy can provide the grasping force feedback function. Future work will focus on improving force feedback performance. This research has no clinical trials.

Event-triggered adaptive neural prescribed performance admittance control for constrained robotic systems without velocity measurements

In this paper, an event-triggered adaptive neural prescribed performance admittance control (ETANPPAC) scheme is proposed to control the constrained robotic systems without velocity sensors. To ensure compliance during human–robot interaction, the reference trajectory is obtained by reshaping the desired trajectory for the robotic systems based on the admittance relationship, where a saturation function is used to constrain the reference trajectory, avoiding excessive contact forces that could render the trajectory inexecutable. Moreover, a barrier Lyapunov function is used to constrain the tracking errors for prescribed performance, where a velocity observer and a radial basis function neural network are designed to estimate the velocity and the uncertainty of the robotic systems, respectively, to enhance control performance. To reduce the communication burden, an event-triggered mechanism is introduced and the Zeno behavior is avoided with the event-triggered condition. The stability of the whole control scheme is analyzed by the Lyapunov function. Simulation and experimental tests demonstrate that the proposed ETANPPAC scheme can track the desired trajectory well under constraints and reduce the communication burden, thereby achieving better efficiency for controlling the robotic systems compared with similar control schemes.

A new active rehabilitation training mode for upper limbs based on Tai Chi Pushing Hands

Robot-assisted rehabilitation is a crucial approach to restoring motor function in the limb. However, the current training trajectory lacks sufficient theoretical or practical support, and the monotony of single-mode training is a concern. Tai Chi Pushing Hands, a beneficial and effective daily exercise, has been shown to improve balance function, psychological state, and motor function of the upper extremities in patients recovering from stroke. To address these issues, we propose a new active rehabilitation training that incorporates Tai Chi Pushing Hands movements and yin-yang balance principles. The training trajectory and direction are encoded by the velocity field and consist of two processes: yang (push) and yin (return). During yang, the limb actively pushes the robot to move, while during yin, the limb actively follows the robot’s movement. To provide necessary assistance, an admittance controller with self-adaptive parameters is designed. In addition, we introduce two indexes, the ‘Intention Angle’ (ϖ) and the time ratio (Γ), to evaluate motion perception performance. Our experiment was conducted on a 4-degree-of-freedom upper limb rehabilitation robot platform, and the subjects were separated into a familiar group and an unfamiliar group. The experiment results show that the training could be completed well no matter whether the subject is familiar with Tai Chi Pushing Hands or not. The parameters and the movement of the robot can be adjusted based on the interactive force to adapt to the ability of the subject.

Open-source design of low-cost sensorised elastic actuators for collaborative prosthetics and orthotics

Collaborative robots, or cobots, have become popular due to their ability to safely operate alongside humans in shared environments. These robots use compliant actuators as a key design element to prevent damage during unintended collisions. In prosthetic and orthotic applications, compliant actuators are crucial for ensuring user safety and comfort. However, most compliant cobots for these applications are excessively expensive and complex to construct. Our study introduces an innovative, cost-effective, and sensorised elastic actuator design tailored for prosthetics and orthotics. The design uses a modular approach and leverages 3D printing technology for rapid customisation, enabling efficient and affordable fabrication. Both hardware and software components are open-source, facilitating unrestricted access for students, researchers, and practitioners. Our design supports impedance and admittance control techniques, enhancing the system’s capabilities. Validation results show a standard deviation of 9.67 Nm between calculated and measured torque in impedance control and 0.2563 radians between calculated and measured angles in admittance control. This allows for improved adaptability to varying operational requirements in prosthetics and orthotics. By introducing this educational framework encompassing a low-cost, sensorised elastic actuator design, we aim to address the need for accessible solutions in the field of collaborative robotics for prosthetics and orthotics.

Modeling and Admittance Control of a Piezoactuated Needle Insertion Device for Safe Puncture of Spinal Membranes

Abstract The most challenging procedure for lumbar puncture (LP) is accurately puncturing the spinal membrane (dura mater) based on an automatic needle insertion device (NID). Piezoactuated NID has shown its advantages in robotic-assisted LP with high precision and compact structure. Soft control of the NID is important for insertion safety; however, for stick-slip piezo-actuated NID, there are few studies due to the complex mechanism of stick-slip motion. Here, a modeling and admittance control method for a proposed stick-slip piezoactuated NID is proposed for safe puncture of the spinal membrane. To analytically model the NID, the compliant mechanism (CM) in the NID is reduced to a second-order system. The stick-slip friction and the spinal membrane are modeled based on the LuGre model and the Hunt-Crossley model, respectively. Based on these models, an admittance controller (AC) for the proposed NID is established to realize the precise control of the position and the safety protection against puncture errors. Simulations and preliminary experiments based on a prototype of the NID and a phantom of the spinal membrane were carried out to test the proposed modeling and control method. Results show that the proposed NID with AC has a maximum insertion error of 0.62 mm and the insertion depth decays by 80% when an unexpected force is applied. Therefore, the proposed model and control method have the potential to be used in real LP procedures by further development.

Neural admittance control based on motion intention estimation and force feedforward compensation for human–robot collaboration

Neural admittance control based on motion intention estimation and force feedforward compensation for human–robot collaboration

An automatic robot for ultrasonic partial discharge detection of gas-insulated switchgear

Purpose Gas-insulated switchgear (GIS) stands as a pivotal component in power systems, susceptible to partial discharge occurrences. Nevertheless, manual inspection proves labor-intensive, exhibits a low defect detection rate. Conventional inspection robots face limitations, unable to perform live line measurements or adapt effectively to diverse environmental conditions. This paper aims to introduce a novel solution: the GIS ultrasonic partial discharge detection robot (GBOT), designed to assume the role of substation personnel in inspection tasks. Design/methodology/approach GBOT is a mobile manipulator system divided into three subsystems: autonomous location and navigation, vision-guided and force-controlled manipulator and data detection and analysis. These subsystems collaborate, incorporating simultaneous localization and mapping, path planning, target recognition and signal processing, admittance control. This paper also introduces a path planning method designed to adapt to the substation environment. In addition, a flexible end effector is designed for full contact between the probe and the device. Findings The robot fulfills the requirements for substation GIS inspections. It can conduct efficient and low-cost path planning with narrow passages in the constructed substation map, realizes a sufficiently stable detection contact and perform high defect detection rate. Practical implications The robot mitigates the labor intensity of grid maintenance personnel, enhances inspection efficiency and safety and advances the intelligence and digitization of power equipment maintenance and monitoring. This research also provides valuable insights for the broader application of mobile manipulators in diverse fields. Originality/value The robot is a mobile manipulator system used in GIS detection, offering a viable alternative to grid personnel for equipment inspections. Comparing with the previous robotic systems, this system can work in live electrical detection, demonstrating robust environmental adaptability and superior efficiency.

Force and time-optimal trajectory planning for dual-arm unilateral cooperative grasping

This paper studies the dual-arm manipulation of an object by means of two collaborative robots. The latter hold the object through limited contact areas, thus applying unilateral contact constraints. This manipulation strategy increases versatility, since it does not require specific grippers depending on the object shape and size. However, to ensure grasping stability (i.e. no slipping of the object), a suitable internal force must be prescribed to ensure the fulfillment of the static-friction condition. In this work, the trend of the internal force is included among the inputs of a time-optimal trajectory planning, in order to find the minimal internal prestress that is able to both satisfy the static-friction condition and manipulate the object in minimal time. Admittance control is used to modulate the forces exerted by the robot end-effectors on the object. An extensive experimentation, on different 6-dimensional trajectories reaching linear and angular accelerations up to 4.5 m/s2 and 7.4 rad/s2, is presented and discussed.

A Perturbation-Robust Framework for Admittance Control of Robotic Systems With High-Stiffness Contacts and Heavy Payload

A Perturbation-Robust Framework for Admittance Control of Robotic Systems With High-Stiffness Contacts and Heavy Payload

Robot Learning Method for Human-like Arm Skills Based on the Hybrid Primitive Framework.

This paper addresses the issue of how to endow robots with motion skills, flexibility, and adaptability similar to human arms. It innovatively proposes a hybrid-primitive-frame-based robot skill learning algorithm and utilizes the policy improvement with a path integral algorithm to optimize the parameters of the hybrid primitive framework, enabling robots to possess skills similar to human arms. Firstly, the end of the robot is dynamically modeled using an admittance control model to give the robot flexibility. Secondly, the dynamic movement primitives are employed to model the robot's motion trajectory. Additionally, novel stiffness primitives and damping primitives are introduced to model the stiffness and damping parameters in the impedance model. The combination of the dynamic movement primitives, stiffness primitives, and damping primitives is called the hybrid primitive framework. Simulated experiments are designed to validate the effectiveness of the hybrid-primitive-frame-based robot skill learning algorithm, including point-to-point motion under external force disturbance and trajectory tracking under variable stiffness conditions.

Development of a Multi-Robot System for Pier Construction

The construction industry is a challenging field for the application of robots. In particular, bridge construction, which involves many tasks at great heights, makes it difficult to implement robots. To construct a bridge, it is necessary to build numerous piers that can support the bridge deck. Pier construction involves a series of tasks including rebar connection, formwork installation, concrete pouring, formwork dismantling, and formwork reinstallation. These activities require working at heights, presenting a significant risk of falls. If bridge construction could be performed remotely using robots instead of relying on human labor, it would greatly contribute to the safety of bridge construction. This paper proposes a multi-robot system capable of remote operation and automation for rebar structure connection, concrete pouring, and concrete vibrating tasks in pier construction. The proposed multi-robot system for pier construction is composed of three robot systems. Each robot system consists of a robot arm mounted on a mobile robot that can move along rails. And to apply the proposed system to a construction site, it is essential to implement a compliance control algorithm that adapts to external forces. In this paper, we propose an admittance control that takes into account the weight of the tool for the compliance control of the proposed robot, which performs tasks by switching between various construction tools of different weights. Furthermore, we propose a synchronization control method for the multi-robot system to connect reinforcing structures. We validated the proposed algorithm through simulation. Furthermore, we developed a prototype of the proposed system to verify the feasibility of the suggested hardware design and control.