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Ozan Çaldiran

dblp:43/7266 · DBLP profile ↗
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3ranked-venue papers
2as first author
1since 2021 · last 2021
0000-0001-6544-0419ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-author · 1 since 2021Systems, architecture and hardware · 1Theory of computation · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%
Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › physical human-robot interaction
admittance control
0.412020
A Variable-Fractional Order Admittance Controller for pHRI · ICRA 2020
Human-robot interaction
physical human-robot interaction
0.412020
A Variable-Fractional Order Admittance Controller for pHRI · ICRA 2020
Robotics › Robot manipulation › industrial robot
collaborative robot
0.112020
A Variable-Fractional Order Admittance Controller for pHRI · ICRA 2020

Methods — techniques the papers use, named apart from their topics

variable admittance control · 0.9fractional order control · 0.9
YearPublicationVenuePosition
2021 Automated Lane Change Decision Making in Highway using a Hybrid Approach
Ozan Çaldiran, Engin Baglayici, Morteza Dousti, Eren Mungan, Enes Emre Bulut, Munire Damla Demir, Furkan Koçyigit
ICINCO1
2020 A Variable-Fractional Order Admittance Controller for pHRI
abstract
In today's automation driven manufacturing environments, emerging technologies like cobots (collaborative robots) and augmented reality interfaces can help integrating humans into the production workflow to benefit from their adaptability and cognitive skills. In such settings, humans are expected to work with robots side by side and physically interact with them. However, the trade-off between stability and transparency is a core challenge in the presence of physical human robot interaction (pHRI). While stability is of utmost importance for safety, transparency is required for fully exploiting the precision and ability of robots in handling labor intensive tasks. In this work, we propose a new variable admittance controller based on fractional order control to handle this trade-off more effectively. We compared the performance of fractional order variable admittance controller with a classical admittance controller with fixed parameters as a baseline and an integer order variable admittance controller during a realistic drilling task. Our comparisons indicate that the proposed controller led to a more transparent interaction compared to the other controllers without sacrificing the stability. We also demonstrate a use case for an augmented reality (AR) headset which can augment human sensory capabilities for reaching a certain drilling depth otherwise not possible without changing the role of the robot as the decision maker.
Doganay Sirintuna, Yusuf Aydin, Ozan Çaldiran, Ozan Tokatli, Volkan Patoglu, Cagatay Basdogan
ICRA3
2009 Bridging the Gap between High-Level Reasoning and Low-Level Control
Ozan Çaldiran, Kadir Haspalamutgil, Abdullah Ok, Can Palaz, Esra Erdem 0001, Volkan Patoglu
LPNMR1