Manipulation of a Mobile Modular Manipulator Interacting With the Environment With the Assistance of Tactile Sensing Feedback

Wang, Jingguo; Li, Yangmin

doi:10.1142/s0219843611002666

Cited by 9 publications

(10 citation statements)

References 19 publications

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“…n,max + w 3 z n,max 𝛽 0 + w 4 𝛽 1 + w 5 z n,max ||v||. Consequently, based on Theorem 1 from Reference 56 with L e (t), L y (t), and L x (t) defined above, we can conclude robust finite-time stability of differentiators ( 43)- (45) for L e = L e (t), L x = L x (t) and L y = L y (t).…”

Section: The State Estimation Problemmentioning

confidence: 81%

“…Second, let us note that controller ( 29) and (30) does not also need force/torque sensors to detect external forces nor adaptive estimation of both disturbances acting on the end-effector and parameters of dynamic equations. Nevertheless, most of the works 45,46 use these sensors and studies 3,15 estimate unknown disturbances as well as need regressor matrix to generate suitable controls. As is known, the construction of regressor matrix is both an ambiguous and time consuming process in practice.…”

Section: Dynamic Controller Of the Mobile Manipulatormentioning

confidence: 99%

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Finite‐time control of mobile manipulators subject to unknown/unstructured external disturbances

Galicki

2022

Intl J Robust & Nonlinear

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A robust finite-time control law is proposed for mobile manipulators with uncertain both kinematic and dynamic equations. Moreover, the following external disturbances are allowed to act on the system: unstructured forces exerted on the end-effector, slip reaction forces affecting the platform wheels, unknown friction forces coming from joints directly driven by the actuators and undesirable unstructured forces caused by singular configurations. In order to cope with both parametric uncertainties and unknown/unstructured external disturbances, we first transform the original control problem whose non-holonomic constraints are violated into a steering one in an extended space of generalized coordinates with extended non-holonomic constraints of the Pfaffian form and then introduce a task space non-singular terminal sliding manifold. Based on the Lyapunov stability theory, a new class of estimated extended transposed Jacobian control laws is derived which both effectively counteract the external forces and significantly reduce the slipping phenomena. A second order sliding technique is involved in our control law to eliminate undesirable chattering effect. An illustrative example of a mobile manipulator control demonstrates the advantages of the approach. Moreover, numerical comparisons with other representative controllers well-known in the literature are also given.

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Section: The State Estimation Problemmentioning

confidence: 81%

Section: Dynamic Controller Of the Mobile Manipulatormentioning

confidence: 99%

Finite‐time control of mobile manipulators subject to unknown/unstructured external disturbances

Galicki

2022

Intl J Robust & Nonlinear

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“…Robotic massage is implemented by a redundant manipulator equipped with a tactile sensor, in which the hybrid impedance control is adopted [8][9][10]. However, traditional medical mechano-therapy theories emphasize on distinguishing the status of various bodies in the therapy process.…”

Section: ⃝Icros Kiee and Springer 2016mentioning

confidence: 99%

Strategies for feet massage robot to position the pelma acupoints with model predictive and real-time optimization

Wei

Gu²,

Xu-jing

et al. 2016

Int. J. Control Autom. Syst.

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It is one of critical factors for a massage robot to find and position the acupuncture point precisely in order to cure the diseases. Based on large amount of sample data offline, Chinese medical empirical knowledge is also introduced to build the prediction model. The massagist prescription and the robot mechanism devise are both considered for robot positioning. Least squares method is of simplicity, easy to use and high efficiency. Its real-time calculation is very effective, too. A modeling method for robot positioning is proposed based on least squares. Knowledge consultation is set for the calculation of acupoint position. The robot needs to get the feature points of a foot to be massaged. The foot contour sampling data are divided into piecewise curve fitting. Qlearning is adopted to optimize the robot positioning for they are model free. CMAC (Cerebellar Model Articulation Controller) cerebellum model is incorporated into the function approximation of Q learning. The learning system is rewarded by referring to the strengths of instrumental signal. By the direct representation, the model of human pelma acupoint is expressed with the vector variables and formal computer language. Through prediction model's calculation, the robot will work out the rough position of acupuncture point. Meanwhile, Q learning does the online adjustment for accurate location. These strategies provide for the robot to automatically search and position the pelma acupoint with little real-time computation and storage. The idea of this paper also prompts a research cue for the development of Chinese medical standardization.

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“…When the design information has been clearly identified, particularly in early design phase, our revised response surface method (RRSM) is suitable for reliable operation of the space manipulator [29]. Robot force/position control under the conditions of the unknown robot parameters is achieved by adaptive fuzzy controller, which is designed to adjust the impedance control parameters based on uncertainty of robot dynamics model compensated by neural network [30,31].…”

Section: Introductionmentioning

confidence: 99%

Dual-layer fuzzy control architecture for the CAS rover arm

Gao

Liu

et al. 2015

Int. J. Control Autom. Syst.

Self Cite

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Since the conventional impedance control method for a rover arm is not suitable for unconstructed environment with uncertainties, a fuzzy inference method which improves the impedance model dynamically is introduced to realize high-precision control. The fuzzy PD control algorithm which applies to the joint control of a rover arm is analyzed in this paper. With the two level control algorithms, a novel dual-layer fuzzy control framework is proposed, which can enhance the control performance significantly. In order to verify the validity and reliability of the designed algorithms, the robotic arm of the CAS rover is considered as an experimental platform. Kinematics and dynamics models of robotic arm are derived at first. Moreover, the fuzzy inference mechanism and implementation process of impedance model parameters are illustrated. Extensive simulations and experimental results show that the control accuracy and the force control of the system have been significantly improved with the proposed dual-layer fuzzy control architecture.

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Manipulation of a Mobile Modular Manipulator Interacting With the Environment With the Assistance of Tactile Sensing Feedback

Cited by 9 publications

References 19 publications

Finite‐time control of mobile manipulators subject to unknown/unstructured external disturbances

Finite‐time control of mobile manipulators subject to unknown/unstructured external disturbances

Strategies for feet massage robot to position the pelma acupoints with model predictive and real-time optimization

Dual-layer fuzzy control architecture for the CAS rover arm

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