Compliance Control and External Force Estimation of 6-DOF Industrial Robots

Liou, Chia-Yu; Wang, Jyun-Hsiang; Chien, Shih-Hsuan; Cheng, Ming-Yang; Tai, Chia-Ying

doi:10.1109/cacs50047.2020.9289770

Cited by 2 publications

(2 citation statements)

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“…where 1 i c are the three centers of high, medium and low hand stiffness, and 2 i c are the three centers of high, medium and low hand damping, as described by (9). In this paper, the hand impedance (i.e.…”

Section: B Fuzzy Rbf Hand Impedance Estimatormentioning

confidence: 99%

“…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%

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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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Section: B Fuzzy Rbf Hand Impedance Estimatormentioning

confidence: 99%