Passivity-based control framework for task-space bilateral teleoperation with parametric uncertainty over unreliable networks

2017 ◽  
Vol 70 ◽  
pp. 187-199 ◽  
Author(s):  
Hsin-Chen Hu ◽  
Yen-Chen Liu
Keyword(s):  
Parametric Uncertainty ◽  
Bilateral Teleoperation ◽  
Task Space ◽  
Unreliable Networks ◽  
Control Framework ◽  
Passivity Based Control

Task-Space Framework for Bilateral Teleoperation With Time Delays

2012 ◽  
Vol 134 (5) ◽  
Author(s):  
Hanlei Wang ◽  
Yongchun Xie
Keyword(s):  
Time Delays ◽  
Joint Space ◽  
Schwarz Inequality ◽  
Bilateral Teleoperation ◽  
Task Space ◽  
Control Approach ◽  
Energy Flows ◽  
Control Framework ◽  
Communication Time ◽  
Task Space Control

This paper investigates the task-space control framework for bilateral teleoperation with communication time delays. Teleoperation in task space R3 × SO(3) presents some distinctive features different from its joint-space counterpart, i.e., SO(3) is nonconvex and bears quite different structure from Euclidean space Rn. Through analyzing the energy flows at the two ports of the teleoperator, we rigorously define the task-space interaction passivity of the teleoperator. Based on this passivity framework, we propose delay-robust control schemes to achieve master–slave position/orientation synchronization. Singularity-free task-space interaction passivity of the closed-loop teleoperator is ensured by the proposed task-space control framework. Using Lyapunov–Krasovskii stability tool and Schwarz inequality, we analyze the performance of the proposed teleoperation control scheme. We also discuss the problems incurred by time-varying delays and the corresponding solutions. Simulation study on a master–slave teleoperator composed of two kinematically dissimilar six-degree of freedom (DOF) manipulators is performed to illustrate the performance of the proposed control approach.

scholarly journals Bilateral teleoperation with object-adaptive mapping

2021 ◽  
Author(s):  
Xiao Gao ◽  
João Silvério ◽  
Sylvain Calinon ◽  
Miao Li ◽  
Xiaohui Xiao
Keyword(s):  
Moving Objects ◽  
Haptic Feedback ◽  
Space Mapping ◽  
Bilateral Teleoperation ◽  
Task Space ◽  
Mapping Approach ◽  
Pick And Place

AbstractTask space mapping approaches for bilateral teleoperation, namely object-centered ones, have yielded the most promising results. In this paper, we propose an invertible mapping approach to realize teleoperation through online motion mapping by taking into account the locations of objects or tools in manipulation skills. It is applied to bilateral teleoperation, with the goal of handling different object/tool/landmark locations in the user and robot workspaces while the remote objects are moving online. The proposed approach can generate trajectories in an online manner to adapt to moving objects, where impedance controllers allow the user to exploit the haptic feedback to teleoperate the robot. Teleoperation experiments of pick-and-place tasks and valve turning tasks are carried out with two 7-axis torque-controlled Panda robots. Our approach shows higher efficiency and adaptability compared with traditional mappings.

Passivity-based control for bilateral teleoperation: A tutorial

Automatica ◽  
2011 ◽  
Vol 47 (3) ◽  
pp. 485-495 ◽  
Author(s):  
Emmanuel Nuño ◽  
Luis Basañez ◽  
Romeo Ortega
Keyword(s):  
Bilateral Teleoperation ◽  
Passivity Based Control

A Synergy-Based Motor Control Framework for the Fast Feedback Control of Musculoskeletal Systems

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
Reza Sharif Razavian ◽  
Borna Ghannadi ◽  
John McPhee
Keyword(s):  
Motor Control ◽  
Feedback Control ◽  
Real Time ◽  
Three Dimensional ◽  
Muscle Synergies ◽  
Task Space ◽  
Computationally Efficient ◽  
Control Framework ◽  
Muscle Activations ◽  
Musculoskeletal Systems

This paper presents a computational framework for the fast feedback control of musculoskeletal systems using muscle synergies. The proposed motor control framework has a hierarchical structure. A feedback controller at the higher level of hierarchy handles the trajectory planning and error compensation in the task space. This high-level task space controller only deals with the task-related kinematic variables, and thus is computationally efficient. The output of the task space controller is a force vector in the task space, which is fed to the low-level controller to be translated into muscle activity commands. Muscle synergies are employed to make this force-to-activation (F2A) mapping computationally efficient. The explicit relationship between the muscle synergies and task space forces allows for the fast estimation of muscle activations that result in the reference force. The synergy-enabled F2A mapping replaces a computationally heavy nonlinear optimization process by a vector decomposition problem that is solvable in real time. The estimation performance of the F2A mapping is evaluated by comparing the F2A-estimated muscle activities against the measured electromyography (EMG) data. The results show that the F2A algorithm can estimate the muscle activations using only the task-related kinematics/dynamics information with ∼70% accuracy. An example predictive simulation is also presented, and the results show that this feedback motor control framework can control arbitrary movements of a three-dimensional (3D) musculoskeletal arm model quickly and near optimally. It is two orders-of-magnitude faster than the optimal controller, with only 12% increase in muscle activities compared to the optimal. The developed motor control model can be used for real-time near-optimal predictive control of musculoskeletal system dynamics.

Wave-Variable Based Force Feedback for a Space-Qualified Telerobot

2008 ◽  
Author(s):  
J. Scot Hart ◽  
Pete Shull ◽  
Diana Gentry ◽  
Gu¨nter Niemeyer ◽  
Stephen Roderick ◽  
...  
Keyword(s):  
Dynamic Capabilities ◽  
Force Feedback ◽  
Contact Forces ◽  
Stable Operation ◽  
Bilateral Teleoperation ◽  
Large Space ◽  
Wave Variable ◽  
Control Framework ◽  
Acceleration Feedback ◽  
Local Feedback

Bilateral teleoperation across significant time delays has been extensively studied and is posed to provide remote control of orbiting robots. Unfortunately, most standard approaches assume an impedance controlled, backdrivable robot. In this work, we apply wave variable control to Ranger, a large, space-qualified, geared robot. We incorporate local feedback of contact forces into the control framework to achieve backdrivable operation. In particular, this control framework imitates an idealized point mass to respect Ranger’s dynamic capabilities. Beyond perceiving steady state contact forces, the user’s perception can be enhanced with high-frequency acceleration feedback of contact transients. Experimental results from controlling Ranger using network communications show stable operation in free space and contact.

scholarly journals Robust Passivity Cascade Technique-Based Control Using RBFN Approximators for the Stabilization of a Cart Inverted Pendulum

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1229
Author(s):  
Reza Rahmani ◽  
Saleh Mobayen ◽  
Afef Fekih ◽  
Jong-Suk Ro
Keyword(s):  
Inverted Pendulum ◽  
Angular Position ◽  
Parametric Uncertainty ◽  
Closed Loop System ◽  
External Disturbances ◽  
Pendulum System ◽  
State Variable ◽  
Inverted Pendulum System ◽  
Control Framework ◽  
Exogenous Disturbances

This paper proposes a novel passivity cascade technique (PCT)-based control for nonlinear inverted pendulum systems. Its main objective is to stabilize the pendulum’s upward states despite uncertainties and exogenous disturbances. The proposed framework combines the estimation properties of radial basis function neural networks (RBFNs) with the passivity attributes of the cascade control framework. The unknown terms of the nonlinear system are estimated using an RBFN approximator. The performance of the closed-loop system is further enhanced by using the integral of angular position as a virtual state variable. The lumped uncertainties (NN—Neural Network approximation, external disturbances and parametric uncertainty) are compensated for by adding a robustifying adaptive rule-based signal to the PCT-based control. The boundedness of the states is confirmed using the passivity theorem. The performance of the proposed approach was assessed using a nonlinear inverted pendulum system under both nominal and disturbed conditions.

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