Browsing by Author "Öztop, Erhan"
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An ecologically valid reference frame for perspective invariant action recognition
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 ... -
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 ... -
Environmental force estimation for a robotic hand : compliant contact detection
Kaya, Osman; Yıldırım, Mehmet Can; Kuzuluk, Nisan; Çiçek, Emre; Bebek, Özkan; Öztop, Erhan; Uğurlu, Regaip Barkan (IEEE, 2015)This paper presents a model based compensation method to enable environmental force estimation for a robotic hand with no tactile or force sensors. To this end, we utilize multi-joint robot dynamics and disturbance observer ... -
Exploration with intrinsic motivation using object–action–outcome latent space
Sener, M. İ.; Nagai, Y.; Öztop, Erhan; Uğur, E. (IEEE, 2023-06)One effective approach for equipping artificial agents with sensorimotor skills is to use self-exploration. To do this efficiently is critical, as time and data collection are costly. In this study, we propose an exploration ... -
Explorations on inverse reinforcement learning for the analysis of motor control and cognitive decision making mechanisms of the brain
Reinforcement Learning is a framework for generating optimal policies given a task and a reward/punishment structure. Likewise, Inverse Reinforcement Learning, as the name suggests, is used for recovering the reasoning ... -
Force reference extraction via human interaction for a robotic polishing task: Force-induced motion
In this paper, a method to control a manipulator using force-induced trajectory is proposed. The trajectory is learned from an operator doing the polishing task using a tool attached to the robot's end-effector. The learning ... -
Forming robot trust in heterogeneous agents during a multimodal interactive game
Kırtay, M.; Öztop, Erhan; Kuhlen, A. K.; Asada, M.; Hafner, V. V. (IEEE, 2022)This study presents a robot trust model based on cognitive load that uses multimodal cues in a learning setting to assess the trustworthiness of heterogeneous interaction partners. As a test-bed, we designed an interactive ... -
Guest editorial special issue on continual unsupervised sensorimotor learning
Navarro-Guerrero, N.; Nguyen, S. M.; Öztop, Erhan; Zhong, J. (IEEE, 2021-06)The pursuit of higher levels of autonomy and versatility in robotics is arguably led by two main factors. First, as we push robots out of the labs and production lines, it becomes increasingly challenging to design for all ... -
High-level features for resource economy and fast learning in skill transfer
Abstraction is an important aspect of intelligence which enables agents to construct robust representations for effective and efficient decision making. Although, deep neural networks are proven to be effective learning ... -
High-level representations through unconstrained sensorimotor learning
Living organisms, in particular mammals are adept at learning complex tasks that may require basic planning such as tool use and manipulation. This ability is manifested by the central nervous system; in particular by the ... -
HMM bazlı 3 boyutlu insan hareketi tanıma ile insan ve robotun ortak çalışması
Pehlivan, Alp Burak; Öztop, Erhan (IEEE, 2014)We offer a system for a human-robot cooperation with natural communication in order to make using of robots in human-interactive tasks easier and more effective. This system includes a system with 3D motion capture cameras, ... -
Human adaptation to human–robot shared control
Amirshirzad, Negin; Kumru, Asiye; Öztop, Erhan (IEEE, 2019-04)Human-in-the-loop robot control systems naturally provide the means for synergistic human-robot collaboration through control sharing. The expectation in such a system is that the strengths of each partner are combined to ... -
Human motor adaptation in whole body motion
Babic, J.; Öztop, Erhan; Kawato, M. (2016)The main role of the sensorimotor system of an organism is to increase the survival of the species. Therefore, to understand the adaptation and optimality mechanisms of motor control, it is necessary to study the sensorimotor ... -
Human movement recognition with dynamic movement primitives
Pehlivan, Alp Burak (2015-09)Dynamic Movement Primitives (DMPs)-originally a method for movement trajectory generation has been also used for recognition tasks. However there has not been a systematic comparison between other recognition methods and ... -
Human-in-the-loop control and task learning for pneumatically actuated muscle based robots
Teramae, T.; Ishihara, K.; Babič, J.; Morimoto, J.; Öztop, Erhan (Frontiers Media, 2018-11-06)Pneumatically actuated muscles (PAMs) provide a low cost, lightweight, and high power-To-weight ratio solution for many robotic applications. In addition, the antagonist pair configuration for robotic arms make it open to ... -
Human-robot collaboration for synergistic task execution
Amirshirzad, Negin (2017-05)There is great potential for human and robot to work together as a team, since this collaboration can take advantage of both human and robot capabilities, cover their weakness and yield a higher performance. We propose and ...
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