Vision-Based Nonlinear Feedback Control of a Ball on Ball System With a Programmable Logic Controller (original) (raw)

Vision for a Robotic Ball Catcher

In this paper we present a system for catching a flying ball with a robot arm using o-the-shelf components (PC based system) for visual tracking. The ball is ob- served by a large baseline stereo camera, comparing each image to a slowly adapting reference image. We track and predict the target position using an Extended Kalman Filter (EKF), also taking into account the air drag. The calibration is achieved by simply perform- ing a few throws and observing their trajectories, as well as moving the robot to some predefined positions. The robustness of the system was demonstrated at the Hannover Fair 2000.

DEVELOPMENT OF A POSITION AND TRAJECTORY TRACKING CONTROL OF BALL AND PLATE SYSTEM USING A DOUBLE FEEDBACK LOOP STRUCTURE

This research work presents the development of a position and trajectory tracking control of ball and plate system. The ball and plate control system was considered as a double feedback loop structure (a loop within a loop), for effective control of the system. The inner loop was designed using linear algebraic method by solving a set of Diophantine equations. The outer loop was designed using H-infinity sensitivity approach. A virtual reality model of the ball and plate system using the virtual reality modelling language (VRML) and graphical user interface (GUI) based simulation model of the system were developed in MATLAB 2013a. The results of the simulation of the system showed that the plate was stabilized at 0.3546 seconds and the ball was able to settle at 1.7087 seconds. The trajectory tracking error of the system using the H-infinity controller was 0.0095 m. The improvements in terms of trajectory tracking error and settling time of the system when compared with the single loop H-infinity (SLH) controller are 71.8% and 60.5% respectively. The improvements when compared with the double loop structure using fuzzy sliding mode controller are 52.5% and 51.2% in terms of the trajectory tracking error and settling time respectively.

O-the-Shelf Vision for a Robotic Ball Catcher

2001

In this paper we present a system for catching a flying ball with a robot arm using o-the-shelf components (PC based system) for visual tracking. The ball is ob- served by a large baseline stereo camera, comparing each image to a slowly adapting reference image. We track and predict the target position using an Extended Kalman Filter (EKF), also taking

Control of a Ball on Sphere System with Adaptive Feedback Linearization Method for Regulation Purpose

MAJLESI JOURNAL OF MECHATRONIC SYSTEMS, 2013

This paper is the nonlinear adaptive feedback linearization control of a class of multi-input multi-output (MIMO) nonlinear systems called “system of ball on a sphere”, which is designed to control and operate a ball on the top of a sphere. Nowadays, Control of nonlinear systems using the feedback linearization has attracted lots of attention in the nonlinear control theory. Since in the general case, there is uncertainty with respect of these nonlinear systems parameters, Adaptive feedback linearization is employed to obtain asymptotically accurate cancellation for this inherent uncertainty The system’s dynamic is described and the equations are illustrated. The results are simulated and compared in toe directions. The outputs are shown in different figures so as to be compared. These simulation results show the exactness of the controller’s performance.

Real-time Ball Detection and Tracking using Raspberry PI

INTEK: Jurnal Penelitian

This paper presents a real-time system for ball detection and tracking system which is reliable in any conditions. Images from the webcam are processed by openCV library running on a Raspberry Pi to move the camera pan and tilt servo and two DC motors to drive the robot body using the Arduino Nano microcontroller. The webcam is integrated in a robot prototype to represent the wheel football robot type. The results show that a ball tracking webcam system is obtained with the capability to detect a ball with a diameter of 17cm within a maximum distance of 200 cm, a stable ball reading when the light intensity is at 32 lux and above. Furthermore, the experimental results demonstrated the system’s robustness in detecting and tracking ball in different distance and ligthing conditions.