Position-based impedance force controller with sensorless force estimation

2019 ◽  
Vol 39 (3) ◽  
pp. 489-496 ◽  
Author(s):  
Jianjun Yuan ◽  
Yingjie Qian ◽  
Liming Gao ◽  
Zhaohan Yuan ◽  
Weiwei Wan
Keyword(s):  
Real Time ◽  
External Force ◽  
Force Control ◽  
Impedance Control ◽  
Surface Shape ◽  
Force Estimation ◽  
Shape Information ◽  
Content Type ◽  
Generalized Inverse Matrix ◽  
Surface Prediction

Purpose This paper aims to purpose an improved sensorless position-based force controller in gravitational direction for applications including polishing, milling and deburring. Design/methodology/approach The first issue is the external force/torque estimation at end-effector. By using motor’s current information and Moore-Penrose generalized inverse matrix, it can be derived from the external torques of every joints for nonsingular cases. The second issue is the force control strategy which is based on position-based impedance control model. Two novel improvements were made to achieve a better performance. One is combination of impedance control and explicit force control. The other one is the real-time prediction of the surface’s shape allowing the controller adaptive to arbitrary surfaces. Findings The result of validation experiments indicates that the estimation of external force and prediction of surface’s shape are credible, and the position-based constant contact force controller in gravitational direction is functional. The accuracy of force tracking is adequate for targeted applications such as polishing, deburring and milling. Originality/value The value of this paper lies in three aspects which are sensorless external force estimation, the combination of impedance control and explicit force control and the independence of surface shape information achieved by real-time surface prediction.

Mechanical Impedance Control of Cooperative Robot During Object Manipulation Based on External Force Estimation Using Recurrent Neural Network

2020 ◽  
Vol 08 (03) ◽  
pp. 239-251
Author(s):  
Misaki Hanafusa ◽  
Jun Ishikawa
Keyword(s):  
Neural Network ◽  
External Force ◽  
Recurrent Neural Network ◽  
Inverse Dynamics ◽  
Impedance Control ◽  
Mechanical Impedance ◽  
Object Manipulation ◽  
Force Estimation ◽  
Dynamics Model ◽  
Compliant Motion

This paper proposes a compliant motion control for human-cooperative robots to absorb collision force when persons accidentally touch the robots even while the robot is manipulating an object. In the proposed method, an external force estimator, which can distinguish the net external force from the object manipulation force, is realized using an inverse dynamics model acquired by a recurrent neural network (RNN). By implementing a mechanical impedance control to the estimated external force, the robot can quickly and precisely carry the object keeping the mechanical impedance control functioned and can generate a compliant motion to the net external force only when the person touches it during manipulation. Since the proposed method estimates the external force from the generalized force based on the learned inverse dynamics, it is not necessary to install any sensors on the manipulated object to measure the external force. This allows the robot to detect the collision even when the person touches anywhere on the manipulated object. The RNN inverse dynamics model is evaluated by the leave-one-out cross-validation and it was found that it works well for unknown trajectories excluded from the learning process. Although the details were omitted due to the limitation of the page length, similar to the simulations, the RNN inverse dynamics model was evaluated using unknown trajectories in the six degree-of-freedom experiments, and it has been verified that it functions properly even for the unknown trajectories. Finally, the validity of the proposed method has been confirmed by experiments in which a person touches a robot while it is manipulating an object with six degrees of freedom.

Impedance control of collaborative robots based on joint torque servo with active disturbance rejection

2019 ◽  
Vol 46 (4) ◽  
pp. 518-528 ◽  
Author(s):  
Tianyu Ren ◽  
Yunfei Dong ◽  
Dan Wu ◽  
Ken Chen
Keyword(s):  
Force Control ◽  
Disturbance Rejection ◽  
Impedance Control ◽  
State Observer ◽  
Extended State Observer ◽  
Joint Torque ◽  
Extended State ◽  
Collaborative Robots ◽  
Content Type ◽  
Control Framework

Purpose The purpose of this paper is to present a simple yet effective force control scheme for collaborative robots by addressing the problem of disturbance rejection in joint torque: inherent actuator flexibility and nonlinear friction. Design/methodology/approach In this paper, a joint torque controller with an extended state observer is used to decouple the joint actuators from the multi-rigid-body system of a constrained robot and compensate the motor friction. Moreover, to realize robot force control, the authors embed this controller into the impedance control framework. Findings Results have been given in simulations and experiments in which the proposed joint torque controller with an extended state observer can effectively estimate and compensate the total disturbance. The overall control framework is analytically proved to be stable, and further it is validated in experiments with a robot testbed. Practical implications With the proposed robot force controller, the robot is able to change its stiffness in real time and therefore take variable tasks without any accessories, such as the RCC or 6-DOF F/T sensor. In addition, programing by demonstration can be realized easily within the proposed framework, which makes the robot accessible to unprofessional users. Originality/value The main contribution of the presented work is the design of a model-free robot force controller with the ability to reject torque disturbances from robot-actuator coupling effect and motor friction, applicable for both constrained and unconstrained environments. Simulation and experiment results from a 7-DOF robot are given to show the effectiveness and robustness of the proposed controller.

Collision detection and force control based on the impedance approach and dynamic modelling

2019 ◽  
Vol 47 (6) ◽  
pp. 813-824
Author(s):  
Pengcheng Wang ◽  
Dengfeng Zhang ◽  
Baochun Lu
Keyword(s):  
Collision Detection ◽  
Force Control ◽  
Control Method ◽  
Impedance Control ◽  
Dynamic Modelling ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Content Type ◽  
Control Approach ◽  
Collision Problem

Purpose This paper aims to address the collision problem between robot and the external environment (including human) in an unstructured situation. A new collision detection and torque optimization control method is proposed. Design/methodology/approach Firstly, when the collision appears, a second-order Taylor observer is proposed to estimate the residual value. Secondly, the band-pass filter is used to reduce the high-frequency torque modeling dynamic uncertainty. With the estimate information and the torque value, a variable impedance control approach is then synthesized to guarantee that the collision is avoided or the collision will be terminated with different contact models and positions. However, in terms of adaptive linear force error, the variation of the thickness of the boundary layer is controlled by the new proximity function. Findings Finally, the experimental results show the better performance of the proposed control method, realizing the force control during the collision process. Originality/value Origin approach and origin experiment.

Sensorless force estimation and control of Delta robot with limited access interface

2018 ◽  
Vol 45 (5) ◽  
pp. 611-622
Author(s):  
Hongtai Cheng ◽  
Hongfei Jiang
Keyword(s):  
Force Control ◽  
High Speed ◽  
Model Parameters ◽  
Force Estimation ◽  
Estimation Model ◽  
Mass Model ◽  
Content Type ◽  
Joint Torques ◽  
Limited Access ◽  
Delta Robot

Purpose Delta robot is a parallel robot specifically designed for high-speed pick and place tasks. However, sometimes they are asked to perform additional assembling and squeezing actions, which is beyond the capability of position-controlled Delta robots. Force sensors may be expensive and add mass to the system. Therefore, the purpose of this paper is to study sensorless force control of Delta robots using limited access interface. Design/methodology/approach Static force analysis is performed to establish a relation between joint torques and external forces. The joint torques are observed from signals provided by motor drivers. A distributed mass model is proposed to compensate the gravity of upper arms and forearms. To minimize the effect of backlash and nonlinear frictions brought by gearboxes, model parameters are calibrated in two separated modes: “LIFTING” and “LOWERING”. Finally, a hybrid force estimation model is built to deal with both cases simultaneously. Surrogate model-based force control law is proposed to increase the force control loop rate and handle the force control problem for discrete position-controlled Delta robots. Findings The results show that the force estimation model is effective and mode separation can significantly improve the accuracy. The force control laws indeed stabilize the robot in desired states. Originality/value The proposed solution is based on position-controlled commercial Delta robot and requires no additional force sensor. It is able to extend Delta robots’ capability and meet requirements of emerging complex tasks.

scholarly journals External force estimation of fracture reduction robot based on force residual method

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141989747
Author(s):  
Jingtao Lei ◽  
Gongliang Zheng ◽  
Lei Hu ◽  
Lihai Zhang ◽  
Tianmiao Wang
Keyword(s):  
Real Time ◽  
External Force ◽  
Estimation Method ◽  
Force Sensor ◽  
Fracture Reduction ◽  
Influence Coefficient ◽  
Force Estimation ◽  
Hill Model ◽  
Vector Method ◽  
Reduction Operation

Robot-assisted fracture reduction surgery should be highly safe and accurate. It is necessary to accurately determine and control the reduction force of the reduction robot. In this article, a fracture reduction robot is designed with the configuration of the 6-universal-prismatic-universal (6-UPU). The vector method is used to analyze the kinematics of the reduction robot. The Jacobian matrix of the reduction robot and the second-order influence coefficient matrix of the acceleration are obtained. The Lagrangian method is adopted to analyze the dynamic of the reduction robot. The muscle contraction force of the femoral shaft fracture is analyzed based on the Hill model to determine the fracture reduction force. According to changing of the reduction force during the fracture reduction operation, a kind of external force estimation method based on force residual analysis is proposed. When there is no external force sensor at the end of the reduction robot, this method can be used to detect the reduction force in real time. According to the displacement, velocity, and output torque of each branch chain, the reduction force during the reduction operation of the reduction robot can be estimated. A simulation system is conducted and the simulation results show that the fracture reduction force can be estimated and accurately tracked in real time, which is of great significance for the safe operation of the fracture reduction robot.

Variable impedance control of finger exoskeleton for hand rehabilitation following stroke

2019 ◽  
Vol 47 (1) ◽  
pp. 23-32
Author(s):  
Fuhai Zhang ◽  
Legeng Lin ◽  
Lei Yang ◽  
Yili Fu
Keyword(s):  
Control System ◽  
Real Time ◽  
Control Method ◽  
Impedance Control ◽  
Contact Forces ◽  
Hand Rehabilitation ◽  
Content Type ◽  
Flexion Extension ◽  
Output Trajectory ◽  
Impedance Parameters

Purpose The purpose of this paper is to propose a variable impedance control method of finger exoskeleton for hand rehabilitation using the contact forces between the finger and the exoskeleton, making the output trajectory of finger exoskeleton comply with the natural flexion-extension (NFE) trajectory accurately and adaptively. Design/methodology/approach This paper presents a variable impedance control method based on fuzzy neural network (FNN). The impedance control system sets the contact forces and joint angles collected by sensors as input. Then it uses the offline-trained FNN system to acquire the impedance parameters in real time, thus realizing tracking the NFE trajectory. K-means clustering method is applied to construct FNN, which can obtain the number of fuzzy rules automatically. Findings The results of simulations and experiments both show that the finger exoskeleton has an accurate output trajectory and an adaptive performance on three subjects with different physiological parameters. The variable impedance control system can drive the finger exoskeleton to comply with the NFE trajectory accurately and adaptively using the continuously changing contact forces. Originality/value The finger is regarded as a part of the control system to get the contact forces between finger and exoskeleton, and the impedance parameters can be updated in real time to make the output trajectory comply with the NFE trajectory accurately and adaptively during the rehabilitation.

scholarly journals Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

2021 ◽  
Author(s):  
Loris Roveda ◽  
Dario Piga
Keyword(s):  
Impedance Control ◽  
Interaction Force ◽  
Industrial Robots ◽  
Force Estimation ◽  
Interaction Control ◽  
Stiffness Properties ◽  
Implementation Effort ◽  
Coupling Dynamics ◽  
And Control ◽  
Assembly Tasks

AbstractIndustrial robots are increasingly used to perform tasks requiring an interaction with the surrounding environment (e.g., assembly tasks). Such environments are usually (partially) unknown to the robot, requiring the implemented controllers to suitably react to the established interaction. Standard controllers require force/torque measurements to close the loop. However, most of the industrial manipulators do not have embedded force/torque sensor(s) and such integration results in additional costs and implementation effort. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper. Relying on sensorless Cartesian impedance control, two Extended Kalman Filters (EKF) are proposed: an EKF for interaction force estimation and an EKF for environment stiffness estimation. Exploiting such estimations, a control architecture is proposed to implement a sensorless force loop (exploiting the provided estimated force) with adaptive Cartesian impedance control and coupling dynamics compensation (exploiting the provided estimated environment stiffness). The described approach has been validated in both simulations and experiments. A Franka EMIKA panda robot has been used. A probing task involving different materials (i.e., with different - unknown - stiffness properties) has been considered to show the capabilities of the developed EKFs (able to converge with limited errors) and control tuning (preserving stability). Additionally, a polishing-like task and an assembly task have been implemented to show the achieved performance of the proposed methodology.

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