Browsing Faculty of Engineering by Author "Asada, M."
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Bimanual rope manipulation skill synthesis through context dependent correction policy learning from human demonstration
Akbulut, B.; Girgin, T.; Mehrabi, Arash; Asada, M.; Ugur, E.; Öztop, Erhan (IEEE, 2023)Learning from demonstration (LfD) with behavior cloning is attractive for its simplicity; however, compounding errors in long and complex skills can be a hindrance. Considering a target skill as a sequence of motor primitives ... -
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 ... -
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 ... -
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 ... -
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 ... -
Imitation and mirror systems in robots through Deep Modality Blending Networks
Seker, M. Y.; Ahmetoglu, A.; Nagai, Y.; Asada, M.; Öztop, Erhan; Ugur, E. (Elsevier, 2022-02)Learning to interact with the environment not only empowers the agent with manipulation capability but also generates information to facilitate building of action understanding and imitation capabilities. This seems to be ... -
Interplay between neural computational energy and multimodal processing in robot-robot interaction
Kırtay, M.; Hafner, V. V.; Asada, M.; Öztop, Erhan (IEEE, 2023)Multimodal learning is an active research area that is gaining importance in human-robot interaction. Despite the obvious benefit of levering multiple sensors for perceiving the world, its neural computational cost has not ... -
Modeling robot trust based on emergent emotion in an interactive task
Kırtay, M.; Öztop, Erhan; Asada, M.; Hafner, V. V. (IEEE, 2021)Trust is an essential component in human-human and human-robot interactions. The factors that play potent roles in these interactions have been an attractive issue in robotics. However, the studies that aim at developing ... -
Multimodal reinforcement learning for partner specific adaptation in robot-multi-robot interaction
Kırtay, M.; Hafner, V. V.; Asada, M.; Kuhlen, A. K.; Öztop, Erhan (IEEE, 2022)Successful and efficient teamwork requires knowledge of the individual team members' expertise. Such knowledge is typically acquired in social interaction and forms the basis for socially intelligent, partner-Adapted ... -
Trust me! I am a robot: an affective computational account of scaffolding in robot-robot interaction
Kırtay, M.; Öztop, Erhan; Asada, M.; Hafner, V. V: (IEEE, 2021-08-08)Forming trust in a biological or artificial interaction partner that provides reliable strategies and employing the learned strategies to scaffold another agent are critical problems that are often addressed separately in ...
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