An Adaptive Control Based Approach For Gripping Novel Objects With Minimal Grasping Force
Abstract
This paper presents the design, analysis, and experimental implementation of an adaptive control to facilitate 1-click grasping of novel objects by a robotic gripper. Motivated by a desire to obtain a reduced-order controller, a previously developed grasp model is reparameterized to design an adaptive backstepping controller. A Lyapunov-based analysis is utilized to show asymptotic convergence of the object slip velocity to the origin. Furthermore, the analysis shows that the closed-loop controller is able to estimate the minimal steady-state force required to grasp the object. Simulation and experiment results both show that the object is immobilized within the gripper without any significant deformation.
Publication Date
8-21-2018
Publication Title
IEEE International Conference on Control and Automation, ICCA
Volume
2018-June
Number of Pages
1040-1045
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICCA.2018.8444179
Copyright Status
Unknown
Socpus ID
85053104376 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85053104376
STARS Citation
Al-Mohammed, Mushtaq; Ding, Z.; Liu, P.; and Behal, A., "An Adaptive Control Based Approach For Gripping Novel Objects With Minimal Grasping Force" (2018). Scopus Export 2015-2019. 8862.
https://stars.library.ucf.edu/scopus2015/8862