This paper presents an on-line estimation method which can find a mathematical expression of stiffness property of the objects grasped in vision-based robotic systems. A robot manipulator in conjunction with visual servo control is applied to autonomously grasp the object. To increase the accuracy of the object compression values associated with the used low-cost hardware, an extended Kalman filter is adopted to fuse the sensing data obtained from webcam and gripper encoder. The grasping forces are measured by a piezoresistive pressure sensor installed on the jaw of the manipulator. The force and position data are used to represent the stiffness property of the grasped objects. An on-line least square algorithm is applied to fit a stiffness equation with time-varying parameters. The experimental results verify the feasibility of the proposed method.
CITATION STYLE
Lin, C. Y., Hung, W. T., & Hsieh, P. J. (2016). Stiffness estimation in vision-based robotic grasping systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9834 LNCS, pp. 279–288). Springer Verlag. https://doi.org/10.1007/978-3-319-43506-0_24
Mendeley helps you to discover research relevant for your work.