EECE@DUTH Robotics Team Papers

The Following papers have been accepted for presentation at the 1st International Conference for Undergraduate and Postgraduate Students in Computer Engineering, Informatics, related Technologies and Applications.

1.Designing and Development of a Puzzle Solver System Using Morphological Associative Memories

In this project a novel approach for solving two-dimensional puzzles and assembling the puzzle using the IR52C robotic arm is presented. When compared to many classical methods for resolving puzzles, the proposed method is characterized by low computational cost and ease of development. In order to achieve shape recognition, classical techniques from the field of image processing are combined with pattern association techniques. A camera captures an image of the whole disassembled puzzle, whose pieces are scattered in the working area of the robotic arm. In the first step, this image is converted to a binary form using Otsu’s method. Then, the connected components are identified and their inclination is corrected. In order to achieve recognition of every single shape, Morphological Associative Memories (ΜΑΜs) that have been previously trained are used. After object recognition, the system communicates with the robotic arm to assemble the pieces of the puzzle. Experimental results demonstrate the effectiveness of the proposed method.

 

2.A Novel Video Summarization Method Based on Compact Composite Descriptors and Fuzzy Classifier

In this paper, a novel method to generate video summaries is proposed, which is allocated mainly for being applied to on-line videos. The novelty of this approach lies in the fact that the authors of this paper transfer the video summarization problem to a single query image retrieval problem. This approach utilizes the recently proposed Compact Composite Descriptors (CCDs) and a fuzzy classifier. In particular, all the video frames are initially sorted according to the distance between an artificially generated, video depended, image. Then the ranking list is classified into a preset number of clusters using the Gustafson Kessel fuzzy classifier. The video abstract is calculated by extracting a representative key frame from every cluster. A significant characteristic of the proposed method is its ability to classify the frames of the video into one or more clusters. Experimental results are presented to indicate the effectiveness of the proposed approach.

 

3.Wired and Wireless Methods for Controlling a 5- DOF Robotic Arm

This paper presents an open-source Graphical User Interface (GUI) that works under the Windows OS (XP or later version) used for controlling a five-degrees-of-freedom robotic arm, including both a virtual remote controller and a command parser. We also provide a control method using a wireless natural-physics controller that translates human-hand movements to commands for the robotic arm. Authors of this paper are using modern console game
controllers that have built-in accelerometers and IR sensors. The resulting methods are tested on Eurobtec’ s IR52c.

 

4.An Open Source Set of Libraries to Control a 5-DOF Robotic Arm

This project introduces a new, open-source, lightweight software library that implements solutions to the Direct and Inverse kinematics problem for a 5-degrees-of-freedom robotic arm in general. In addition, a library for low level communication with the IR25c robotic arm has been developed, that can be used with the previously mentioned library and allows for easy manipulation of the robot. Both libraries are open source software, provided under the GNU General Public License and are designed with modularity in mind, so that they can be used together or separately in large projects. Download