Abstract
New applications related to robotic manipulation or transportation tasks, with or without physical grasping, are continuously being developed. To perform these activities, the robot takes advantage of different kinds of perceptions. One of the key perceptions in robotics is vision. However, some problems related to image processing makes the application of visual information within robot control algorithms difficult. Camera-based systems have inherent errors that affect the quality and reliability of the information obtained. The need of correcting image distortion slows down image parameter computing, which decreases performance of control algorithms. In this paper, a new approach to correcting several sources of visual distortions on images in only one computing step is proposed. The goal of this system/algorithm is the computation of the tilt angle of an object transported by a robot, minimizing image inherent errors and increasing computing speed. After capturing the image, the computer system extracts the angle using a Fuzzy filter that corrects at the same time all possible distortions, obtaining the real angle in only one processing step. This filter has been developed by the means of Neuro-Fuzzy learning techniques, using datasets with information obtained from real experiments. In this way, the computing time has been decreased and the performance of the application has been improved. The resulting algorithm has been tried out experimentally in robot transportation tasks in the humanoid robot TEO (Task Environment Operator) from the University Carlos III of Madrid.
Highlights
Advances in robotics technology are encouraging the development of novel applications and new tasks to be accomplished by humanoid robots
We find those centered around manipulation, which can be classified into two main groups: grasping tasks, in which the way to grab an object by the hand of a humanoid robot is studied [1,2] and non-grasping tasks
The images obtained with the robot camera were post-processed following the steps named and the information extracted from those images was stored in an input dataset, which was processed by the Fuzzy filter
Summary
Advances in robotics technology are encouraging the development of novel applications and new tasks to be accomplished by humanoid robots Among these new tasks, we find those centered around manipulation, which can be classified into two main groups: grasping tasks, in which the way to grab an object by the hand of a humanoid robot is studied [1,2] and non-grasping tasks. Some of the techniques that we found implement a correction by comparing images obtained from different points of view (stereo-images) [9], whereas, in others, the correction is achieved by adjusting images from uncalibrated cameras [10] Another example is the research developed in [11], in which the perspective error in different kinds of images is well corrected. Different problems were found and the image rectification approach was discarded
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