Estimation of camera-space manipulation parameters by means of an extended Kalman filter: Applications to parallel robots. (23rd April 2019)

• Record Type: Journal Article
• Authors: González, Alejandro; Gonzalez-Galvan, Emilio J; Maya, Mauro; Cardenas, Antonio; Piovesan, Davide
• Is Part Of: International journal of advanced robotic systems. Volume 16:Number 2(2019:Mar./Apr.)
• Publication Date: 2019-04-23
• Subjects: Vision-based control -- camera-space manipulation -- extended Kalman filter -- parallel robot; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881419842987
• Languages: English
• ISSNs: 1729-8806

Abstract

Parallel robots have a growing range of applications due to their appealing characteristics (high speed and acceleration, increased rigidity, etc.). However, several open problems make it difficult to model and control them. Low computational-cost algorithms are needed for high speed tasks where high accelerations are required. This article develops the nonlinear camera-space manipulation method and makes use of an extended Kalman filter (EKF) for the estimation of the camera-space manipulation parameters. This is presented as an alternative to the traditional method which can be time consuming while reaching convergence. The proposed camera-space manipulation parameter identification was performed in positioning tasks for a parallel manipulator and the experimental results are reported. Results show that it is possible to estimate the set of camera-space manipulation parameters by means of an extended Kalman filter. Using the proposed Kalman filter method we observed a significant reduction of the computational effort when estimating the camera-space manipulation parameters. However, there was no significant reduction of the robot's positioning error. The proposed extended Kalman filter implementation requires only 2 ms to update the camera-space manipulation parameters compared to the 85 ms required by the traditional camera-space manipulation algorithm. Such time reduction is beneficial for the implementation of the method for a wide range of high speed and industrial applications. This article presents a novel use of an extended Kalman filter for the real-time estimation of the camera-space manipulation parameters and shows that it can be used to increase the positioning accuracy of a parallel robot.