Performance Comparisons of Different Observer-Based Force-Sensorless Approaches for Impedance Control of Collaborative Robot Manipulators

Chien, Shih-Hsuan; Wang, Jyun-Hsiang; Cheng, Ming-Yang

doi:10.1109/icps48405.2020.9274790

Cited by 10 publications

(2 citation statements)

References 22 publications

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“…The typical observers selected in this paper are identified according to the following procedures. First, a list of observers is collected based on three recent review papers [8][9][10] and one research paper [11]. Then, the following two rules are applied: (a) the observer is applicable in practice in a physical robotic system and (b) the observer is independent of the controllers, that is, not relying on a specific controller.…”

Section: Introductionmentioning

confidence: 99%

A brief survey of observers for disturbance estimation and compensation

Li,

Xing,

Hashemi

et al. 2023

Robotica

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An accurate dynamic model of a robot is fundamentally important for a control system, while uncertainties residing in the model are inevitable in a physical robot system. The uncertainties can be categorized as internal disturbances and external disturbances in general. The former may include dynamic model errors and joint frictions, while the latter may include external payloads or human-exerted force to the robot. Disturbance observer is an important technique to estimate and compensate for the uncertainties of the dynamic model. Different types of disturbance observers have been developed to estimate the lumped uncertainties so far. In this paper, we conducted a brief survey on five typical types of observers from a perspective of practical implementation in a robot control system, including generalized momentum observer (GMO), joint velocity observer (JVOB), nonlinear disturbance observer (NDOB), disturbance Kalman filter (DKF), and extended state observer (ESO). First, we introduced the basics of each observer including equations and derivations. Two common types of disturbances are considered as two scenarios, that is, constant external disturbance and time-varying external disturbance. Then, the observers are separately implemented in each of the two simulated scenarios, and the disturbance tracking performance of each observer is presented while their performance in the same scenario has also been compared in the same figure. Finally, the main features and possible behaviors of each type of observer are summarized and discussed. This survey is devoted to helping readers learn the basic expressions of five typical observers and implement them in a robot control system.

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Section: Introductionmentioning

confidence: 99%

A brief survey of observers for disturbance estimation and compensation

Li,

Xing,

Hashemi

et al. 2023

Robotica

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“…During these tasks, human operators need to interact with the robot for a long period of time. Impedance control [4]- [6] or admittance control [7]- [9] is usually implemented to ensure compliant motion of the robot. Some tasks such as manual welding [10] or laparoscopic training [11] require the robot to perform with precision and minimize energy consumption of the operator.…”

Section: Introductionmentioning

confidence: 99%

Robotic Assistance for Physical Human–Robot Interaction Using a Fuzzy RBF Hand Impedance Compensator and a Neural Network Based Human Motion Intention Estimator

Chien

Wang

Cheng³

2021

IEEE Access

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This paper proposes a robotic assistance control scheme for intuitive teaching tasks by integrating the motion intention of human and real-time hand impedance compensation based upon a fuzzy RBF (Radial Basis Function) compensator. The motion intention of a human is estimated using a feedforward neural network. The parameters of the proposed fuzzy RBF hand impedance compensator are adjusted by considering hand impedance and robot dynamics. Three robotic assistance control schemes are compared: 1) robot without an impedance compensator; 2) robot with a constant-parameter impedance compensator; 3) robot with a fuzzy RBF hand impedance compensator. Several experiments have been conducted to verify the effectiveness of the proposed approach by comparing the contour error, exerted force and task time spent on teaching tasks. Experimental results indicate that the proposed fuzzy RBF hand impedance compensator has the best assistance results among the tested robotic assistance control schemes.

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