Investigation of a new method for improving image resolution for camera tracking applications

Camera based systems have been a preferred choice in many motion tracking applications due to the ease of installation and the ability to work in unprepared environments. The concept of these systems is based on extracting image information (colour and shape properties) to detect the object location. However, the resolution of the image and the camera field-of- view (FOV) are two main factors that can restrict the tracking applications for which these systems can be used. Resolution can be addressed partially by using higher resolution cameras but this may not always be possible or cost effective. This research paper investigates a new method utilising averaging of offset images to improve the effective resolution using a standard camera. The initial results show that the minimum detectable position change of a tracked object could be improved by up to 4 times

A new strategy for improving vision based tracking accuracy based on utilization of camera calibration information

Abstract— Camera calibration is one of the essential components of a vision based tracking system where the objective is to extract three dimensional information from a set of two dimensional frames. The information extracted from the calibration process is significant for examining the accuracy of the vision sensor, and thus further for estimating its effectiveness as a tracking system in real applications. This paper introduces another use for this information in which the proper location of the camera can be predicted. Anew mathematical formula based on utilizing the extracted calibration information was used for finding the optimum location for the camera, which provides the best detection accuracy. Moreover, the calibration information was also used for selecting the proper image Denoising filter. The results obtained proved the validity of the proposed formula in finding the desired camera location where the smallest detection errors can be produced. Also, results showed that the proper selection of the filter parameters led to a considerable enhancement in the overall accuracy of the camera, reducing the overall detection error by 0.2 mm

3D Visual Tracking of an Articulated Robot in Precision Automated Tasks

Abstract: The most compelling requirements for visual tracking systems are a high detection accuracy and an adequate processing speed. However, the combination between the two requirements in real world applications is very challenging due to the fact that more accurate tracking tasks often require longer processing times, while quicker responses for the tracking system are more prone to errors, therefore a trade-off between accuracy and speed, and vice versa is required. This paper aims to achieve the two requirements together by implementing an accurate and time efficient tracking system. In this paper, an eye-to-hand visual system that has the ability to automatically track a moving target is introduced. An enhanced Circular Hough Transform (CHT) is employed for estimating the trajectory of a spherical target in three dimensions, the colour feature of the target was carefully selected by using a new colour selection process, the process relies on the use of a colour segmentation method (Delta E) with the CHT algorithm for finding the proper colour of the tracked target, the target was attached to the six degree of freedom (DOF) robot end-effector that performs a pick-and-place task. A cooperation of two Eye-to Hand cameras with their image Averaging filters are used for obtaining clear and steady images. This paper also examines a new technique for generating and controlling the observation search window in order to increase the computational speed of the tracking system, the techniques is named Controllable Region of interest based on Circular Hough Transform (CRCHT). Moreover, a new mathematical formula is introduced for updating the depth information of the vision system during the object tracking process. For more reliable and accurate tracking, a simplex optimization technique was employed for the calculation of the parameters for camera to robotic transformation matrix. The results obtained show the applicability of the proposed approach to track the moving robot with an overall tracking error of 0.25 mm. Also, the effectiveness of CRCHT technique in saving up to 60% of the overall time required for image processing

Assessment of the positioning accuracy of a small articulated robot during machining operations

The application of industrial robots for machining of complex parts is a very promising field that refers to the ability of the robot to produce parts with complex geometries that typically requires multi-axes machine tools. However, there are many restrictions that limit the use of robot in advanced manufacturing industry such as positioning errors and low stiffness. This work investigates the positioning accuracy and the path repeatability of a Mitsubishi RV-1A robot with six degree of freedom during machining movements by using a Faro laser tracker. The results obtained show a significant motion error caused by the robot, even with the absence of cutting force. A comparison has been made between the positions of the commanded path measurements taken by the robot controller and the actual position of the end effector of the robot measured by the tracker