Compliant Force Sensor-Less Capture of an Object in Orbit

Although tendon-driven continuum manipulators have been extensively researched, how to realize tip contact force sensing in a more general and efficient way without increasing the diameter is still a challenge. Rather than use a complex modeling approach, this paper proposes a general tip contact force-sensing method based on a recurrent neural network that takes the tendons’ position and tension as the input of a recurrent neural network and the tip contact force of the continuum manipulator as the output and fits this static model by means of machine learning so that it may be used as a real-time contact force estimator. We also designed and built a corresponding three-degree-of-freedom contact force data acquisition platform based on the structure of a continuum manipulator designed in our previous studies. After obtaining training data, we built and compared the performances of a multi-layer perceptron-based contact force estimator as a baseline and three typical recurrent neural network-based contact force estimators through TensorFlow framework to verify the feasibility of this method. We also proposed a manually decoupled sub-estimators algorithm and evaluated the advantages and disadvantages of those two methods.

PurposeComponent positioning is an important part of aircraft assembly, aiming at the problem that it is difficult to accurately fall into the corresponding ball socket for the ball head connected with aircraft component. This study aims to propose a ball head adaptive positioning method based on impedance control.Design/methodology/approachFirst, a target impedance model for ball head positioning is constructed, and a reference positioning trajectory is generated online based on the contact force between the ball head and the ball socket. Second, the target impedance parameters were optimized based on the artificial fish swarm algorithm. Third, to improve the robustness of the impedance controller in unknown environments, a controller is designed based on model reference adaptive control (MRAC) theory and an adaptive impedance control model is built in the Simulink environment. Finally, a series of ball head positioning experiments are carried out.FindingsDuring the positioning of the ball head, the contact force between the ball head and the ball socket is maintained at a low level. After the positioning, the horizontal contact force between the ball head and the socket is less than 2 N. When the position of the contact environment has the same change during ball head positioning, the contact force between the ball head and the ball socket under standard impedance control will increase to 44 N, while the contact force of the ball head and the ball socket under adaptive impedance control will only increase to 19 N.Originality/valueIn this paper, impedance control is used to decouple the force-position relationship of the ball head during positioning, which makes the entire process of ball head positioning complete under low stress conditions. At the same time, by constructing an adaptive impedance controller based on MRAC, the robustness of the positioning system under changes in the contact environment position is greatly improved.

It is well known that space robots play a significant role in the human space activities. Capturing a free floating object in space is one of important missions assigned to space robots and it has increasingly attracted researchers’ attention recently. In this paper, the dynamics and control of capturing a floating rigid body using a space robot are investigated. The dynamic model of the system is established by the single direction recursive construction method and the Jourdain’s velocity variation principle. The contact force between space robots and targets has been set up based on the Hertz contact theory. Then the influence on the whole system incurred by this contact force has been thoroughly analyzed through simulations of both central and eccentric impact. Our simulation result verified the impact on the whole system caused by the contact force, and it also indicated the extreme complexity of the dynamic response caused by impact during the capture process. The space robot base attitude has been controlled using the controller based on the nonlinear decoupling method. Our simulation results showed adequate effectiveness.

One of the most important phases of satellite servicing operations by a space robot is the "contact" phase. During the contact between the end-effector and grasping point, there is a risk that the target and the robot can be pushed away from each other by the contact force. Therefore, the method to control the end-effector by the impedance control so as not to deflect the target was suggested. However, all of real control systems have the control time delay. In case of the target capture operation, the time delay of the impedance control makes the impulse of the contact larger. In this paper, to verify the effect of the time delay of the impedance control, experiments with a air-floating testbed and numerical simulations are carried out.

An investigation on the relationship between grip, push and contact forces applied to a tool handle

Physiotherapy is the treatment to recover a patient’s mobility and limb function after an injury, illness, or disability. Rehabilitation robots can be used to replace human physiotherapists. To ensure safety during robot physical therapy, the patient’s limb needs to be controlled to track a desired joint trajectory, and the torque due to interaction force/torque needs to be measured and regulated. Therefore, hybrid impedance and admittance with position control (HIPC) is required to track the trajectory and simultaneously regulate the contact torque. The literature describes two structures of HIPC: (1) a switched framework between admittance and impedance control operating in parallel (HIPCSW); and (2) a series connection between admittance and impedance control without switching. In this study, a hybrid adaptive impedance and position-based admittance control (HAIPC) in series is developed, which consists of a proportional derivative-based admittance position controller with gravitational torque compensation and an adaptive impedance controller. An extended state observer is used to estimate the interaction joint torque due to human stiff contact with the exoskeleton without the use of force/torque sensor, which is then used in the adaptive algorithm to update the stiffness and damping gains of the adaptive impedance controller. Simulation results obtained using MATLAB show that the proposed HAIPC significantly reduces the mean absolute values of the actuation torques (control inputs) required for the shoulder and elbow joints in comparison with HIPC and HIPCSW.

In this paper, an image-based impedance control strategy for force tracking of an unmanned aerial manipulator (UAM) is presented. Firstly, image features with nice decoupling characteristics are designed and the relationship between the camera motion and the image features is derived. Then, a two-stage strategy is proposed to achieve force tracking of the UAM on a planar object in an arbitrary pose. The first stage drives the end-effector perpendicular to the object’s planer surface by pure visual servoing. To achieve force tracking under the visual guidance, an adaptive visual impedance control method which adjusts the target stiffness according to the force tracking error and the visual feature error is proposed in the second stage. The closed-loop system is proved asymptotically stable by means of Lyapunov analysis. Further, the stability in free flight phase of the stage two is also analyzed and ensured. Finally, experiments were carried out including a whiteboard cleaning task in different poses. The experimental results illustrate the validity and effectiveness of the proposed approach. Note to Practitioners—This work is motivated by the contact force tracking problem of an unmanned aerial manipulator (UAM) without the position measurement. In recent years, impedance control is widely used in force tracking problems. However, position measurement is needed both for the robot and the object in most studies. To generate desired force under visual guidance, image-based visual servoing is combined with a novel impedance controller with variable stiffness. The idea is intuitive. For a human in contact with a wall, the contact force is controlled by adjusting his arm stiffness, which means the stiffness is adapted to the difference between the desired and actual contact force. Furthermore, the stiffness is also adapted to the visual tracking error, removing the assumption that no tracking error is in the inner loop of the impedance controller in the previous works. The proposed strategy is a promising solution for real applications and is validated by a board cleaning experiment in this paper.

ABSTRACTA robot interacting with the environment requires that the end effector \\hboxposition is tracked and that the forces of contact are kept below certain reference values. For instance, in a rehabilitation session using a robotic device, the contact forces are limited by the allowed strength of the human limbs and their complex-joints. In these cases, a control scheme which considers both position and force control is essential to avoid damage to either the end effector or the object interacting with the robot. This paper therefore develops a real-time force/position control scheme for a three-DOF parallel robot whose end effector holds a DOF one translation (1 T) and two rotations (2 R). The implemented hybrid force/position control considers, as a reference, the normal force on the mobile platform, which is measured by means of a load cell installed on the platform. The position control is designed to track the orientations of the robot either in joint or task space using a model-based control scheme with identified parameters. Moreover, the force control is based on a PD action. The control scheme is developed through simulations, before being applied to an actual parallel robot. The findings show that with the implemented controller, the actual robot accomplishes the reference values for the normal force on the mobile platform, while at the same time the platform accurately follows the required angular orientation.

In general, the contact force, which is used in controller design for robotic compliant motion, can be either explicitly calculated through complicated computation or measured by expensive force sensors. A force control strategy using the estimated contact force is proposed. The estimation of the contact force and states is primarily based on their previous observer design. It is shown that the controller achieves asymptotic stability.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

An impedance force control framework that enables precise contact force tracking for industrial robots subject to unknown environment dynamics is proposed in this paper. First, a position-based impedance controller is formulated and theoretical analysis reveals that perfect force tracking requires exact knowledge of the environment stiffness and contact position—quantities that are rarely available in practice. To compensate for these uncertainties, a Unified Residual Compensation Iterative Learning Control (URC-ILC) scheme is introduced. Instead of estimating each environment parameter separately, URC-ILC aggregates all modeling errors into a single residual term, which is iteratively updated and fed forward to the impedance loop, guaranteeing stable convergence of the contact force. The controller parameters are tuned off-line by Multi-Directional Particle Swarm Optimization (MDPSO) algorithm, which is developed by (i) injecting four performance-oriented velocity components—response speed, steady-state error, oscillation, and overshoot—into the swarm dynamics, (ii) modulating the inertia weight through a sigmoid schedule, and (iii) applying a mutation operator that prevents premature convergence. Simulations show that MDPSO converges faster and attains higher accuracy than the classical PSO. Experiments further demonstrate that the URC-ILC-based impedance controller, with parameters optimized by MDPSO, reduces steady-state force error by 44.38% relative to the conventional impedance strategy. These results confirm the effectiveness of the proposed approach for high-precision, compliant robotic machining under uncertain contact conditions.

Contact behaviors of medical devices, such as guidewires and catheters, are critical in endovascular surgeries. In this work, a new method to predict adhesive contact force between catheter and vascular artery is presented. Multi-asperity adhesion on the surface of vascular artery, deformation of asperity and deformation of vascular substrate are all considered. The single asperity behavior is described with Johnson-Kendall-Roberts (JKR) contact model. The multi-asperity behavior is based on Greenwood-Williamson (GW) asperity model. Vascular substrate is considered as elastic bulk substrate and its deformation is determined with Hertzian pressure from asperity on a circular region on the elastic half space. The model shows that the deformation of vascular substrate accounts for the majority of the total contact deformation and significantly affects the predicted contact force. The model is verified with published experimental data. The comparison shows that the model produces very accurate prediction of contact force between catheter and vascular artery when the contact force is compressive. Parametric analysis based on asperity topography is carried out. The analysis shows that the diameter of the circular region of the interface between asperity and vascular substrate has more significant effect on the estimation of contact force than the radius of asperity. Further validation of prediction accuracy of the model under experiment is needed.

As the manipulation object of a patient transfer robot is a human, which can be considered a complex and time-varying system, motion adjustment of a patient transfer robot is inevitable and essential for ensuring patient safety and comfort. This paper proposes a motion adjustment method based on a two-level deep neural network (DNN) and a greedy algorithm. First, a dataset including information about human posture and contact forces is collected by experiment. Then, the DNN, which is used to estimate contact force, is established and trained with the collected datasets. Furthermore, the adjustment is conducted by comparing the estimated contact force of the next state and the real contact force of the current state by a greedy algorithm. To assess the validity, first, we employed the DNN to estimate contact force and obtained the accuracy and speed of 84% and 30 ms, respectively (implemented with an affordable processing unit). Then, we applied the greedy algorithm to a dual-arm transfer robot and found that the motion adjustment could reduce the contact force and improve human comfort efficiently; these validated the effectiveness of our proposal and provided a new approach to adjust the posture of the care receiver for improving their comfort through reducing the contact force between human and robot.

To ensure efficient transportation of large space structures in the future, it has been suggested that they be transported in an unassembled and compact form and then assembled inorbit using space robots. Forces generated during open contact operations have to be taken into careful consideration so that structural components can be successfully acquired and assembled by the robot. Unlike ground-based robots, the free-flying space robot base will deviate from its desired orientation when the spacecraft comes in contact with structural elements. This effect on spacecraft attitude may adversely affect communication, solar energy collection and in extreme cases the stability of the spacecraft. While thrusters can be used to provide regulation torques, in a scenario where the spacecraft is surrounded by structural components that are to be assembled, filing clusters is undesirable. Further, the force impulses generated by thrusters have poor resolution and hence are unsuitable for providing fine regulation. In this paper, the authors utilize reaction wheels (RWs) to provide accurate and smooth control torques without the need to have on-board fuel. By adopting the commonly used canonical-form dynamic model of a space robot as found in the literature, force tracking may be achieved, but a desired orientation of the spacecraft cannot be guaranteed. To solve this problem, the authors build dynamic equations of the space manipulator and the spacecraft base separately to form basis for separate contact-force control and attitude control of the platform. By taking a further step from previous literature which mainly try to maintain contact between the end-effector and the target, hybrid force/motion control is extended to a space robot in this paper in order to track a desired force trajectory and simultaneously maintain a desired relative position between the end-effector and the target to avoid inducing tumbling torques. A recently proposed adaptive variable structure control method is applied to design a robust attitude controller taking into account system uncertainties and external disturbances. A two-link planar space robot model is simulated to track a desired uni-axial contact force and regulate the spacecraft attitude during contact with a free-floating target. The simulation results have demonstrated better robustness and performance of the proposed controller, such as shorter settling time in the presence of disturbance and smaller force tracking error, in comparison to a conventional feedback linearisation attitude controller.

In this research, a virtual simulator (slave system) of an eight-degrees-of-freedom robot (two-DOF crane, one-DOF prismatic (telescopic mast), and five-DOF robot manipulator) is developed and teleoperated by an external hardware haptic device (master system) for nuclear power plant's (NPP) reactor vessel internals (RVI) dismantling operations. For operations such as cutting, the robot end-effector with a laser cutter should maintain a constant distance from the physical wall of RVI. So, a virtual wall near the physical wall is assumed. The end-effector should remain on the virtual wall for optimal cutting which is achieved through force tracking impedance control. In this paper, initially sliding mode control (SMC) was implemented but resulted in chattering in force tracking response. Therefore, super twisting sliding mode control (STSMC)-based force tracking impedance control is designed and implemented for enhanced end-effector force tracking. The control input of the STSMC is composed of a continuous and discrete component. Continuous control input regulates control performance against uncertainties, whereas discrete provides a switching algorithm. STSMC then eliminates the chattering effect and reduces the force tracking error. The performance of SMC-based and STSMC-based impedance control is compared, and the comparison shows that the STSMC-based impedance control provides enhanced performance.

Reference trajectory learning based adaptive iterative impedance control for a lower limb rehabilitation exoskeleton with actuator saturation