In this paper, an admittance controller based on a gray prediction model is designed for end-effector gripping force. The gray prediction model is used to predict environmental parameters in real-time and dynamically adjusts the reference position to reduce the steady-state force error. In this way, the dynamic response capability of impedance control can be improved, and its steady-state force error is also reduced. To this end, the designed method can grasp soft objects with unknown characteristics. The algorithm is validated by simulation experiments, which provide a theoretical basis for flexible fruit grasping.
Grasp Compliant Control Using Adaptive Admittance Control Methods for Flexible Objects
Lect.Notes Computer
International Conference on Intelligent Robotics and Applications ; 2023 ; Hangzhou, China July 05, 2023 - July 07, 2023
2023-10-21
11 pages
Article/Chapter (Book)
Electronic Resource
English
Robotic grasp , Flexible objects , Admittance control , Compliant control Computer Science , Artificial Intelligence , Software Engineering/Programming and Operating Systems , Computer Applications , Computer Communication Networks , Special Purpose and Application-Based Systems , User Interfaces and Human Computer Interaction
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