My research interests are Bio-inspired Robotics, Swarm Intelligence,Software Engineering for Robotics, Simulation Systems andComputational modeling of brain regions / mechanisms.
If you are an undergraduate student interested in robotics, send me an e-mail or drop by Ozu Robotics Laboratory any time.
“Research is hard. Extending human knowledge is a difficult task. Discovering new and useful ideas is like attacking a granite cliff with your bare hands. Once in a while a small fragment breaks loose and progress is made” D. S. Bernstein.
Up until now, I was privileged to be a member of four robotics research groups namely Swarm Systems Research Laboratory at TOBB University of Economics and Technology, Bilkent Dexterous Robotics and Locomotion (BDRL), OzU-Robotics Laboratory and Robotics Research Group of the DIEI (Cassino, Italy). In these research groups, I have actively participated in research projects which are listed below.
Emergent Emotion on a Humanoid Robot Platform, (ongoing)
This paper presents our initial work on how emotion based behaviors may emerge through computational mechanisms. We hold that in addition to basic emotions such as anger and fear that serves bodily well being of the organism, high level emotions such as boredom and affection have evolved to facilitate low cost brain computations. In large and complex brains (e.g. primate brains), the neuronal energy consumption for cognition is non-negligible. We propose that for such organisms computational regulatory mechanisms for decision making give rise to behaviors that can be explained by various emotional states. As a proof of concept for this idea, we envision a robotic cognitive system and a select function that we assign a neural cost for its operation. To be concrete, we use a small humanoid robot platform (Darwin-OP) and implement a neural network (Hopfield Network) that allows the robot to recall learned patterns that it sees through its camera. As a model of neural computational energy consumption, we postulate that a change in the state of a neural unit of the network consumes one unit of (neural) energy. Therefore, the total computational energy consumed is determined by the incoming stimuli. The robot is programmed to avoid high energy consumption by showing aversive behavior when the energy consumption is high. Otherwise, the robot demonstrates engaging behavior. For an external observer these responses may be perceived as robot’s having certain emotional (affectional) preference for input stimuli. In this article in addition to robot experiments, we also emphasize the biological support for our proposal and provide detailed exposition of biological background and its relevance for the hypothesis that (certain) emotions may emerge through computational mechanisms. Click here for a demo movie.
Control of networked cooperative teams of mobile robots (May- August 2013)
In this project, the experiments with laser equipped Khepera III robots were carried out to create robust wireless connectivity by estimating some channel parameters in online while navigating in the dynamic environments- corridors and lab space- and executing a specific task. In this research period, we provide initial results of the multi and single robot experimental studies. The obtained results seem to be promising and collected data can be used as a benchmark after quantitatively analysing parameters and distance/time relations. To extend this study, the multiple robot experiments will be carried out in the same environment and the connectivity parameters will be extracted in real-time. The extracted parameters will enable the robots to update their own positions to maintain connectivity between two end points of the network which are base-station and leading robot. Click here for a project website.
In these projects we describe implementations of various bio-inspired algorithms for obtaining the chemical gas concentration map of an environment filled with a contaminant. The experiments are performed using Khepera III miniature mobile robots equipped with a “kheNose” transducer in an environment with ethanol gas. We implement and investigate the performance of Decentralized and Asynchronous Particle Swarm Optimization (DAPSO), Bacterial Foraging Optimization (BFO), and Ant Colony Optimization (ACO) algorithms. Moreover, we implement sweeping (sequential search algorithm) as a base case for comparison with the implemented algorithms. During the experiments at each step the robots send their sensor readings and position data to a remote computer where these data are combined, filtered, and interpolated to form the chemical concentration map of the environment. The robots also exchange this information among each other and cooperate in the DAPSO and ACO algorithms. The performance of the implemented algorithms is compared in terms of the quality of the maps obtained and success of locating the target gas sources.
Non-linear Function minimization, (July-August 2010)
In this project, I have partially coded and modified a genetic algorithms to minimize a non-linear function, this function can be any functions which has non-linear characteristic such as distance among agents in dynamic environment and concentration value of chemically contaminated environment. The algorithm can be implemented in different applications. (see Biomimicry for Optimization, Automation and Control)
Laser Based Map Building, (Feb-June 2011)
The main purpose of this project is to generate online 2D map of unknown environment via random walk, wall following, sweeping and bionic algorithms. The other objective of this project is to make performance comparison of algorithms in terms of extracted maps. The project is successfully finished by using free/open source software and satisfied applied software engineering procedures. The software development environments: Player/Stage, Ubuntu/Debian, C/C++, gnuPlot, Doxygen and Emacs.
Kırtay, M. & Öztop, E. (2013, May). Emergent Emotion via Neural Computational Energy Conservation on a Humanoid Robot. (Accepted for publication in the Proceedings of 2013 IEEE-RAS International Conference on Humanoid Robots)
Turduev, M., Cabrita, G., Kırtay, M., Gazi, V., & Marques, L. (2012, December).Experimental studies on chemical concentration map building by a multi-robot system using bio-inspired algorithms. Journal of Autonomous Agents and Multi- Agent Systems (JAAMAS 2012). DOI: 10.1007/s10458-012-9213-x
Turduev, M., Kırtay, M., Sousa, P., Gazi, V., & Marques, L. (2010, October). Chemical concentration map building through bacterial foraging optimization based search algorithm by mobile robots. In IEEE International Conference on Systems, Man, and Cybernetics (SMC 2010) (pp. 32423249). Istanbul, Turkey. DOI:10.1109/ICSMC.2010.5642297
Kırtay, M., Turduev, M., Sousa, P., Gazi, V., & Marques, L. (2010, September). Chemical concentration map building through ant colony optimization based search algorithm. In Turkish National Conference on Automotic Control (TOK 2010) (pp. 180186). Kocaeli, Turkey (in Turkish).