Adaptive Impedance-controlled Manipulator Based on Collision Detection

Huang, Jianbin; Xie, Zongwu; Jin, Minghe; Zainan, Jiang; Liu, Hong

doi:10.1016/s1000-9361(08)60075-8

Cited by 24 publications

(8 citation statements)

References 15 publications

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“…Therefore, the applications of human-robot interaction (HRI) have become a new development domain and direction [6,7]. It is necessary to develop an interaction control method that achieves position tracking and reliably adapts the force exerted on the environment in order to avoid damage both in the environment and in the manipulator itself [8].…”

Section: Introductionmentioning

confidence: 99%

Position/Force Tracking Impedance Control for Robotic Systems with Uncertainties Based on Adaptive Jacobian and Neural Network

Peng

Yang

2019

Complexity

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In this paper, an adaptive Jacobian and neural network based position/force tracking impedance control scheme is proposed for controlling robotic systems with uncertainties and external disturbances. To achieve precise force control performance indirectly by using the position tracking, the control scheme is divided into two parts: the outer-loop force impedance control and the inner-loop position tracking control. In the outer-loop, an improved impedance controller, which combines the traditional impedance relationship with the PID-like scheme, is designed to eliminate the force tracking error quickly and to reduce the force overshoot effectively. In this way, the satisfied force tracking performance can be achieved when the manipulator contacts with environment. In the inner-loop, an adaptive Jacobian method is proposed to estimate the velocities and interaction torques of the end-effector due to the system kinematical uncertainties, and the system dynamical uncertainties and the uncertain term of adaptive Jacobian are compensated by an adaptive radial basis function neural network (RBFNN). Then, a robust term is designed to compensate the external disturbances and the approximation errors of RBFNN. In this way, the command position trajectories generated from the outer-loop force impedance controller can be then tracked so that the contact force tracking performance can be achieved indirectly in the forced direction. Based on the Lyapunov stability theorem, it is proved that all the signals in closed-loop system are bounded and the position and velocity errors are asymptotic convergence to zero. Finally, the validity of the control scheme is shown by computer simulation on a two-link robotic manipulator.

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Section: Introductionmentioning

confidence: 99%

Position/Force Tracking Impedance Control for Robotic Systems with Uncertainties Based on Adaptive Jacobian and Neural Network

Peng

Yang

2019

Complexity

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“…Zhu et al [16], [17] and Koivumäki and Mattila [18] introduced VDC into the control systems of modular robots, flexible-joint-based robots, and hydraulic-driving robots. Huang et al [19] achieved adaptive impedance control and collision detection based on a VDC-based dynamic model and control theory; simulation and experimental results have proven the effectiveness of this method.…”

Section: Introductionmentioning

confidence: 99%

Virtual Decomposition Based Modeling for Multi-DOF Manipulator With Flexible Joint

et al. 2019

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This paper discusses a problem that has plagued researchers for a long time regarding the dynamic modeling of a multiple degree-of-freedom (multi-DOF) manipulator such that its manipulation exhibits a higher computational efficiency and accuracy. Unknown friction, unknown gravitational torque, an uncertain moment of inertia, and severe joint coupling are the primary disturbing factors in multi-DOF manipulator modeling. In addition, joint flexible problems caused by the integration of harmonic drives increase the modeling complexity. Hitherto, no effective method has been found to address these problems. The virtual decomposition (VD)-based method exhibits the advantages of joint dynamics decoupling and minor computation compared with the traditional Lagrangian formulation or Newton-Euler formulation. In this study, an estimation method for the deformation-related torque of harmonic drives is established based on a novel experimental model; subsequently, this method is utilized in the VD-based model for the multi-DOF manipulator. Hence, the decoupling dynamic model for the manipulator considering joint flexibility is established. The performance of this new method has been evaluated by a contrast simulation with the Newton-Euler formulation, and the multi-DOF manipulator control simulation and experiment have been conducted with a VD-based model as a feedforward compensator to verify its performance in real-time control. The results demonstrated the validity and efficiency of e proposed approach.

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“…The main limitation of most impedance control schemes is the need for precise knowledge of the parameters and the dynamic model of the robotic system to control. That is why some adaptive/robust impedance controllers have been developed (Carelli and Kelly, 1991;Lu and Meng, 1991;Chien and Huang, 2004;Jiang, 2005;Jianbin et al, 2009;Kang et al, 2009;Xu et al, 2011;Gribovskaya et al, 2011;Sharifi et al, 2012;Hussain et al, 2013;Pérez-Ibarra et al, 2014, Li et al, 2017He et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…In order to restrict contact forces, a collision detection system with joint torque sensors was proposed by Jianbin et al (2009) by generating an adaptive Cartesian impedance control for flexible joint manipulators.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Impedance Control of Robot Manipulators with Parametric Uncertainty for Constrained Path–Tracking

Bonilla

Mendoza

Campos-Delgado

et al. 2018

International Journal of Applied Mathematics and Computer Science

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The main impedance control schemes in the task space require accurate knowledge of the kinematics and dynamics of the robotic system to be controlled. In order to eliminate this dependence and preserve the structure of this kind of algorithms, this paper presents an adaptive impedance control approach to robot manipulators with kinematic and dynamic parametric uncertainty. The proposed scheme is an inverse dynamics control law that leads to the closed-loop system having a PD structure whose equilibrium point converges asymptotically to zero according to the formal stability analysis in the Lyapunov sense. In addition, the general structure of the scheme is composed of continuous functions and includes the modeling of most of the physical phenomena present in the dynamics of the robotic system. The main feature of this control scheme is that it allows precise path tracking in both free and constrained spaces (if the robot is in contact with the environment). The proper behavior of the closed-loop system is validated using a two degree-of-freedom robotic arm. For this benchmark good results were obtained and the control objective was achieved despite neglecting non modeled dynamics, such as viscous and Coulomb friction.

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Adaptive Impedance-controlled Manipulator Based on Collision Detection

Cited by 24 publications

References 15 publications

Position/Force Tracking Impedance Control for Robotic Systems with Uncertainties Based on Adaptive Jacobian and Neural Network

Position/Force Tracking Impedance Control for Robotic Systems with Uncertainties Based on Adaptive Jacobian and Neural Network

Virtual Decomposition Based Modeling for Multi-DOF Manipulator With Flexible Joint

Adaptive Impedance Control of Robot Manipulators with Parametric Uncertainty for Constrained Path–Tracking

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