Browsing Computer Science by OzU Authors "Öztop, Erhan"
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ACNMP: skill transfer and task extrapolation through learning from demonstration and reinforcement learning via representation sharing
Akbulut, M. T.; Öztop, Erhan; Xue, H.; Tekden, A. E.; Şeker, M. Y.; Uğur, E. (ML Research Press, 2020)To equip robots with dexterous skills, an effective approach is to first transfer the desired skill via Learning from Demonstration (LfD), then let the robot improve it by self-exploration via Reinforcement Learning (RL). ... -
Action and language mechanisms in the brain: data, models and neuroinformatics
Arbib, M. A.; Bonaiuto, J. J.; Bornkessel-Schlesewsky, I.; Kemmerer, D.; MacWhinney, B.; Årup Nielsen, F.; Öztop, Erhan (Springer Science+Business Media, 2014-01)We assess the challenges of studying action and language mechanisms in the brain, both singly and in relation to each other to provide a novel perspective on neuroinformatics, integrating the development of databases for ... -
Adaptive inverse kinematics of a 9-DOF surgical robot for effective manipulation
Sunal, Begüm; Öztop, Erhan; Bebek, Özkan (IEEE, 2019)In a robotic-assisted surgical system, fine and precise movement is essential. However, when the user wishes to cover a wider area during tele-operation, the configuration designed for precise motion may restrict the user ... -
Adaptive shared control with human intention estimation for human agent collaboration
Amirshirzad, Negin; Uğur, E.; Bebek, Özkan; Öztop, Erhan (IEEE, 2022)In this paper an adaptive shared control frame-work for human agent collaboration is introduced. In this framework the agent predicts the human intention with a confidence factor that also serves as the control blending ... -
Advancing humanoid robots for social integration: Evaluating trustworthiness through a social cognitive framework
Taliaronak, V.; Lange, A. L.; Kırtay, M.; Öztop, Erhan (IEEE, 2023)Trust is an essential concept for human-human and human-robot interactions. Yet only a few studies have addressed this concept from a robot perspective - that is, forming robot trust in interaction partners. Our previous ... -
Affordance-based altruistic robotic architecture for human–robot collaboration
Imre, M.; Öztop, Erhan; Nagai, Y.; Ugur, E. (Sage, 2019-08)This article proposes a computational model for altruistic behavior, shows its implementation on a physical robot, and presents the results of human-robot interaction experiments conducted with the implemented system. ... -
Algorithms for obtaining parsimonious higher order neurons
Sezener, C. E.; Öztop, Erhan (Springer International Publishing, 2017)Most neurons in the central nervous system exhibit all-or-none firing behavior. This makes Boolean Functions (BFs) tractable candidates for representing computations performed by neurons, especially at finer time scales, ... -
Cognition-enabled robot manipulation in human environments: requirements, recent work, and open problems
Ersen, M.; Öztop, Erhan; Sariel, S. (IEEE, 2017-09)Service robots are expected to play an important role in our daily lives as our companions in home and work environments in the near future. An important requirement for fulfilling this expectation is to equip robots with ... -
Combined weight and density bounds on the polynomial threshold function representation of Boolean functions
Öztop, Erhan; Asada, M. (Elsevier, 2022-08)In an earlier report it was shown that an arbitrary n-variable Boolean function f can be represented as a polynomial threshold function (PTF) with 0.75×2n or less number of monomials. In this report, we derive an upper ... -
Cooperative multi-task assignment for heterogonous UAVs
Özalp, N.; Ayan, U.; Öztop, Erhan (IEEE, 2015)This research is focused on the cooperative multi-task assignment problem for heterogeneous UAVs, where a set of multiple tasks, each requiring a predetermined number of UAVs, have to be completed at specific locations. ... -
Deep multi-object symbol learning with self-attention based predictors
Ahmetoğlu, A.; Öztop, Erhan; Uğur, E. (IEEE, 2023)This paper proposes an architecture that can learn symbolic representations from the continuous sensorimotor experience of a robot interacting with a varying number of objects. Unlike previous works, this work aims to ... -
Deepsym: Deep symbol generation and rule learning for planning from unsupervised robot interaction
Ahmetoglu, A.; Seker, M. Y.; Piater, J.; Öztop, Erhan; Ugur, E. (AI Access Foundation, 2022)Symbolic planning and reasoning are powerful tools for robots tackling complex tasks. However, the need to manually design the symbols restrict their applicability, especially for robots that are expected to act in open-ended ... -
Developmental scaffolding with large language models
Çelik, B.; Ahmetoglu, A.; Ugur, E.; Öztop, Erhan (IEEE, 2023)Exploration and self-observation are key mechanisms of infant sensorimotor development. These processes are further guided by parental scaffolding to accelerate skill and knowledge acquisition. In developmental robotics, ... -
Discovering predictive relational object symbols with symbolic attentive layers
Ahmetoglu, A.; Celik, B.; Öztop, Erhan; Uğur, E. (IEEE, 2024-02-01)In this letter, we propose and realize a new deep learning architecture for discovering symbolic representations for objects and their relations based on the self-supervised continuous interaction of a manipulator robot ... -
Dynamic movement primitives for human movement recognition
Pehlivan, Alp Burak; Öztop, Erhan (IEEE, 2015)Dynamic Movement Primitives (DMPs)-originally a method for movement trajectory generation [1] has been also used for recognition tasks [2, 3]. However there has not been a systematic comparison between other recognition ... -
An ecologically valid reference frame for perspective invariant action recognition
Bayram, Berkay; Uğur, E.; Asada, M.; Öztop, Erhan (IEEE, 2021)In robotics, objects and body parts can be represented in various coordinate frames to ease computation. In biological systems, body or body part centered coordinate frames have been proposed as possible reference frames ... -
Effect regulated projection of robot’s action space for production and prediction of manipulation primitives through learning progress and predictability based exploration
Bugur, S.; Öztop, Erhan; Nagai, Y.; Ugur, E. (IEEE, 2021-06)In this study, we propose an effective action parameter exploration mechanism that enables efficient discovery of robot actions through interacting with objects in a simulated table-top environment. For this, the robot ... -
Effective robot skill synthesis via divided control
Kaya, Osman; Öztop, Erhan (IEEE, 2018-07-02)Learning from demonstration is a powerful method for obtaining task skills, which aim to eliminate the need for explicit robot programming. Classically, the tasks are demonstrated to the robot by means of either recorded ... -
Emergent emotion via neural computational energy conservation on a humanoid robot
Kırtay, Murat; Öztop, Erhan (IEEE, 2013)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, ... -
Emotion as an emergent phenomenon of the neurocomputational energy regulation mechanism of a cognitive agent in a decision-making task
Kırtay, M.; Vannucci, L.; Albanese, U.; Laschi, C.; Öztop, Erhan; Falotico, E. (Sage, 2021-02)Biological agents need to complete perception-action cycles to perform various cognitive and biological tasks such as maximizing their wellbeing and their chances of genetic continuation. However, the processes performed ...
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