Publications

Sliwowski, D. J., & Lee, D. (2025). ConditionNET: Learning Preconditions and Effects for Execution Monitoring. IEEE Robotics and Automation Letters, 10(2), 1337–1344. https://doi.org/10.1109/LRA.2024.3520916
| ConditionNET: Learning Preconditions and Effects for Execution Monitoring at reposiTUm , opens an external URL in a new window

Kim, D., Park, S.-S., Lee, K.-H., Lee, D., & Ryu, J.-H. (2024). Is a Simulation better than Teleoperation for Acquiring Human Manipulation Skill Data? In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 5182–5188). https://doi.org/10.1109/IROS58592.2024.10801865
| Is a Simulation better than Teleoperation for Acquiring Human Manipulation Skill Data? at reposiTUm , opens an external URL in a new window
Egle, T., Yan, Y., Lee, D., & Ott, C. (2024). Enhancing Model-Based Step Adaptation for Push Recovery through Reinforcement Learning of Step Timing and Region. In 2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids) (pp. 165–172). IEEE. https://doi.org/10.34726/8160
| Enhancing Model-Based Step Adaptation for Push Recovery through Reinforcement Learning of Step Timing and Region at reposiTUm , opens an external URL in a new window
Mascaro, E. V., & Lee, D. (2024). Know your limits! Optimize the robot’s behavior through self-awareness. In E. Yoshida (Ed.), 2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids) (pp. 258–265). https://doi.org/10.1109/Humanoids58906.2024.10769929
| Know your limits! Optimize the robot’s behavior through self-awareness at reposiTUm , opens an external URL in a new window
Arduini, R., Michel, Y., Singh, H., Klodmann, J., & Lee, D. (2024). Learning From Demonstration of Robot Motions And Stiffness Behaviors For Surgical Blunt Dissection. In 2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN) (pp. 1491–1496). https://doi.org/10.1109/RO-MAN60168.2024.10731313
| Learning From Demonstration of Robot Motions And Stiffness Behaviors For Surgical Blunt Dissection at reposiTUm , opens an external URL in a new window
Schulleri, K., Feizian, F., Steinböck, M., Lee, D., & Johannsen, L. (2024). Does vibrotactile biofeedback for postural control interfere with cognitive processes? Journal of NeuroEngineering and Rehabilitation, 21(1), Article 184. https://doi.org/10.1186/s12984-024-01476-w
| Does vibrotactile biofeedback for postural control interfere with cognitive processes? at reposiTUm , opens an external URL in a new window
Valls Mascaro, E., & Lee, D. (2024, October 1). Know your limits! Optimize the robot’s behavior through self-awareness. 17th International Workshop on Human-Friendly Robotics (HFR 2024), Lugano, Switzerland.
| Know your limits! Optimize the robot’s behavior through self-awareness at reposiTUm , opens an external URL in a new window
Jadav, S. V., Heidersberger, J., Ott, C., & Lee, D. (2024). Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations. In 2024 IEEE International Conference on Robotics and Automation (ICRA) (pp. 15151–15157). https://doi.org/10.1109/ICRA57147.2024.10610761
| Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations at reposiTUm , opens an external URL in a new window
Mascaro, E. V., Yan, Y., & Lee, D. (2024). Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction. In M. O’Malley (Ed.), 2024 IEEE International Conference on Robotics and Automation (ICRA) (pp. 17264–17271). IEEE. https://doi.org/10.1109/ICRA57147.2024.10610682
| Robot Interaction Behavior Generation based on Social Motion Forecasting for Human-Robot Interaction at reposiTUm , opens an external URL in a new window
Michel, Y., Saveriano, M., & Lee, D. (2024). A Novel Safety-Aware Energy Tank Formulation Based on Control Barrier Functions. IEEE Robotics and Automation Letters, 9(6), 5206–5213. https://doi.org/10.1109/LRA.2024.3389556
| A Novel Safety-Aware Energy Tank Formulation Based on Control Barrier Functions at reposiTUm , opens an external URL in a new window
Mascaro, E. V., Ahn, H., & Lee, D. (2024). A Unified Masked Autoencoder with Patchified Skeletons for Motion Synthesis. In M. Wooldridge (Ed.), Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI 2024) (pp. 5261–5269). AAAI Press. https://doi.org/10.1609/aaai.v38i6.28333
| A Unified Masked Autoencoder with Patchified Skeletons for Motion Synthesis at reposiTUm , opens an external URL in a new window
Eiband, T., Lay, F., Nottensteiner, K., & Lee, D. (2024). Unifying skill-based programming and programming by demonstration through ontologies. In 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023) (pp. 595–605). Elsevier. https://doi.org/10.1016/j.procs.2024.01.059
| Unifying skill-based programming and programming by demonstration through ontologies at reposiTUm , opens an external URL in a new window
Kowalski, V., Eiband, T., & Lee, D. (2024). Kinesthetic Skill Refinement for Error Recovery in Skill-Based Robotic Systems. In 2024 21st International Conference on Ubiquitous Robots (UR) (pp. 27–34). https://doi.org/10.1109/UR61395.2024.10597483
| Kinesthetic Skill Refinement for Error Recovery in Skill-Based Robotic Systems at reposiTUm , opens an external URL in a new window
Pantano, M., Klass, V., Yang, Q., Sathuluri, A., Regulin, D., Janisch, L., Zimmermann, M., & Lee, D. (2024). Simplifying Robot Grasping in Manufacturing with a Teaching Approach based on a Novel User Grasp Metric. In 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023) (pp. 1961–1971). Elsevier B.V. https://doi.org/10.1016/j.procs.2024.02.018
| Simplifying Robot Grasping in Manufacturing with a Teaching Approach based on a Novel User Grasp Metric at reposiTUm , opens an external URL in a new window
Visconti, E., Bartocci, E., Falcone, Y., & Nenzi, L. (2024). Adaptable Configuration of Decentralized Monitors. In V. Castiglioni & A. Francalanza (Eds.), Formal Techniques for Distributed Objects, Components, and Systems. FORTE 2024 (pp. 197–217). Springer. https://doi.org/10.1007/978-3-031-62645-6_11
| Adaptable Configuration of Decentralized Monitors at reposiTUm , opens an external URL in a new window

An, S., Park, G., & Lee, D. (2023). Strictly Positive Realness-Based Feedback Gain Design Under Imperfect Input-Output Feedback Linearization in Prioritized Control Problem. In 2023 62nd IEEE Conference on Decision and Control (CDC) (pp. 2622–2629). https://doi.org/10.1109/CDC49753.2023.10383658
| Strictly Positive Realness-Based Feedback Gain Design Under Imperfect Input-Output Feedback Linearization in Prioritized Control Problem at reposiTUm , opens an external URL in a new window
Michel, Y., Saveriano, M., Abu-Dakka, F. J., & Lee, D. (2023). Orientation Control with Variable Stiffness Dynamical Systems. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4457–4463). IEEE. https://doi.org/10.1109/IROS55552.2023.10342531
| Orientation Control with Variable Stiffness Dynamical Systems at reposiTUm , opens an external URL in a new window
Stoiber, M., Elsayed, M., Reichert, A. E., Steidle, F., Lee, D., & Triebel, R. (2023). Fusing Visual Appearance and Geometry for Multi-Modality 6DoF Object Tracking. In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 1170–1177). IEEE. https://doi.org/10.1109/IROS55552.2023.10341961
| Fusing Visual Appearance and Geometry for Multi-Modality 6DoF Object Tracking at reposiTUm , opens an external URL in a new window
Michel, Y., Li, Z., & Lee, D. (2023). A Learning-Based Shared Control Approach for Contact Tasks. IEEE Robotics and Automation Letters, 8(12), 8002–8009. https://doi.org/10.1109/LRA.2023.3322332
| A Learning-Based Shared Control Approach for Contact Tasks at reposiTUm , opens an external URL in a new window
Pantano, M., Curioni, A., Regulin, D., Kamps, T., & Lee, D. (2023). Effects of Robotic Expertise and Task Knowledge on Physical Ergonomics and Joint Efficiency in a Human-Robot Collaboration Task. In 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids). 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids), Austin, United States of America (the). IEEE. https://doi.org/10.1109/Humanoids57100.2023.10375163
| Effects of Robotic Expertise and Task Knowledge on Physical Ergonomics and Joint Efficiency in a Human-Robot Collaboration Task at reposiTUm , opens an external URL in a new window
Xue, H., Michel, Y., & Lee, D. (2023). A Shared Control Approach Based on First-Order Dynamical Systems and Closed-Loop Variable Stiffness Control. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 109(4), Article 85. https://doi.org/10.1007/s10846-023-02023-w
| A Shared Control Approach Based on First-Order Dynamical Systems and Closed-Loop Variable Stiffness Control at reposiTUm , opens an external URL in a new window
Mascaro, E. V., Sliwowski, D., & Lee, D. (2023). HOI4ABOT: Human-Object Interaction Anticipation for Human Intention Reading Collaborative roBOTs. In J. Tan, M. Toussaint, & K. Darvish (Eds.), Volume 229: Conference on Robot Learning, 6-9 November 2023, Atlanta, USA (pp. 1111–1130). PMLR.
| HOI4ABOT: Human-Object Interaction Anticipation for Human Intention Reading Collaborative roBOTs at reposiTUm , opens an external URL in a new window
Michel, Y., Saveriano, M., & Lee, D. (2023). A Passivity-Based Approach for Variable Stiffness Control With Dynamical Systems. IEEE Transactions on Automation Science and Engineering. https://doi.org/10.1109/TASE.2023.3324141
| A Passivity-Based Approach for Variable Stiffness Control With Dynamical Systems at reposiTUm , opens an external URL in a new window
Ahn, H., Michel, Y., Eiband, T., & Lee, D. (2023). Vision-Based Approximate Estimation of Muscle Activation Patterns for Tele-Impedance. IEEE Robotics and Automation Letters, 8(8), 5220–5227. https://doi.org/10.1109/LRA.2023.3293275
| Vision-Based Approximate Estimation of Muscle Activation Patterns for Tele-Impedance at reposiTUm , opens an external URL in a new window
Ni, Z., Valls Mascaro, E., Ahn, H., & Lee, D. (2023). Human–object interaction prediction in videos through gaze following. Computer Vision and Image Understanding, 233, Article 103741. https://doi.org/10.1016/j.cviu.2023.103741
| Human–object interaction prediction in videos through gaze following at reposiTUm , opens an external URL in a new window
Paulius, D., Agostini, A., & Lee, D. (2023). Long-Horizon Planning and Execution With Functional Object-Oriented Networks. IEEE Robotics and Automation Letters, 8(8), 4513–4520. https://doi.org/10.1109/LRA.2023.3285510
| Long-Horizon Planning and Execution With Functional Object-Oriented Networks at reposiTUm , opens an external URL in a new window
Reisch, R. T., Pantano, M., Janisch, L., Knoll, A., & Lee, D. (2023). Spatial Annotation of Time Series for Data Driven Quality Assurance in Additive Manufacturing. In R. Teti & D. D’Addona (Eds.), Procedia CIRP : 16th CIRP Conference on Intelligent Computation in Manufacturing Engineering (pp. 753–758). Elsevier BV. https://doi.org/10.1016/j.procir.2023.06.129
| Spatial Annotation of Time Series for Data Driven Quality Assurance in Additive Manufacturing at reposiTUm , opens an external URL in a new window
Michel, Y., Schulleri, K., Johannsen, L., & Lee, D. (2023). Coordination tending towards an anti-phase relationship determines greater sway reduction during entrainment with a simulated partner. Human Movement Science, 89, Article 103090. https://doi.org/10.1016/j.humov.2023.103090
| Coordination tending towards an anti-phase relationship determines greater sway reduction during entrainment with a simulated partner at reposiTUm , opens an external URL in a new window
Eiband, T., Liebl, J., Willibald, C., & Lee, D. (2023). Online task segmentation by merging symbolic and data-driven skill recognition during kinesthetic teaching. Robotics and Autonomous Systems, 162, Article 104367. https://doi.org/10.34726/3503
| Online task segmentation by merging symbolic and data-driven skill recognition during kinesthetic teaching at reposiTUm , opens an external URL in a new window
Caporali, A., Pantano, M., Janisch, L., Regulin, D., Palli, G., & Lee, D. (2023). A Weakly Supervised Semi-Automatic Image Labeling Approach for Deformable Linear Objects. IEEE Robotics and Automation Letters, 8(2), 1013–1020. https://doi.org/10.1109/LRA.2023.3234799
| A Weakly Supervised Semi-Automatic Image Labeling Approach for Deformable Linear Objects at reposiTUm , opens an external URL in a new window
Valls Mascaro, E., Ahn, H., & Lee, D. (2023). Intention-Conditioned Long-Term Human Egocentric Action Forecasting. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (pp. 6048–6057). https://doi.org/10.1109/WACV56688.2023.00599
| Intention-Conditioned Long-Term Human Egocentric Action Forecasting at reposiTUm , opens an external URL in a new window
Ahn, H., Mascaro, E. V., & Lee, D. (2023). Can We Use Diffusion Probabilistic Models for 3D Motion Prediction? In ICRA 2023 : conference proceedings : 29th May-2nd June 2023, ExCeL London : IEEE International Conference on Robotics and Automation / IEEE Robotics & Automation Society, IEEE (pp. 9837–9843). https://doi.org/10.1109/ICRA48891.2023.10160722
| Can We Use Diffusion Probabilistic Models for 3D Motion Prediction? at reposiTUm , opens an external URL in a new window
Yan, Y., Mascaro, E. V., & Lee, D. (2023). ImitationNet: Unsupervised Human-to-Robot Motion Retargeting via Shared Latent Space. In 2023 IEEE-RAS 22nd International Conference on Humanoid Robots (Humanoids) (pp. 1–8). IEEE. https://doi.org/10.1109/Humanoids57100.2023.10375150
| ImitationNet: Unsupervised Human-to-Robot Motion Retargeting via Shared Latent Space at reposiTUm , opens an external URL in a new window

Willibald, C., & Lee, D. (2022). Multi-Level Task Learning Based on Intention and Constraint Inference for Autonomous Robotic Manipulation. In IROS 2022 Kyōto - IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 7688–7695). https://doi.org/10.1109/IROS47612.2022.9981288
| Multi-Level Task Learning Based on Intention and Constraint Inference for Autonomous Robotic Manipulation at reposiTUm , opens an external URL in a new window
Yang, C., Luo, S., Lepora, N., Ficuciello, F., Lee, D., Wan, W., & Su, C.-Y. (2022). Biomimetic Perception, Cognition, and Control: From Nature to Robots [From the Guest Editors]. IEEE Robotics and Automation Magazine, 29(4), 8–8. https://doi.org/10.1109/MRA.2022.3213199
| Biomimetic Perception, Cognition, and Control: From Nature to Robots [From the Guest Editors] at reposiTUm , opens an external URL in a new window
Eiband, T., Willibald, C., Tannert, I., Weber, B., & Lee, D. (2022). Collaborative programming of robotic task decisions and recovery behaviors. Autonomous Robots. https://doi.org/10.1007/s10514-022-10062-9
| Collaborative programming of robotic task decisions and recovery behaviors at reposiTUm , opens an external URL in a new window
Mascaro, E. V., Shuo Ma, Ahn Hyemin, & Lee, D. (2022). Robust Human Motion Forecasting using Transformer-based Model. In 022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 10674–10680). IEEE. https://doi.org/10.1109/IROS47612.2022.9981877
| Robust Human Motion Forecasting using Transformer-based Model at reposiTUm , opens an external URL in a new window
Pantano, M., Yang, Q., Blumberg, A., Reisch, R., Hauser, T., Lutz, B., Regulin, D., Kamps, T., Traganos, K., & Lee, D. (2022). Influence of task decision autonomy on physical ergonomics and robot performances in an industrial human-robot collaboration scenario. Frontiers in Robotics and AI, 9, Article 943261. https://doi.org/10.3389/frobt.2022.943261
| Influence of task decision autonomy on physical ergonomics and robot performances in an industrial human-robot collaboration scenario at reposiTUm , opens an external URL in a new window
Pantano, M., Eiband, T., & Lee, D. (2022). Capability-based Frameworks for Industrial Robot Skills: a Survey. In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (pp. 2355–2362). https://doi.org/10.1109/CASE49997.2022.9926648
| Capability-based Frameworks for Industrial Robot Skills: a Survey at reposiTUm , opens an external URL in a new window
Murali, P. K., Wang, C., Lee, D., Dahiya, R., & Kaboli, M. (2022). Deep Active Cross-Modal Visuo-Tactile Transfer Learning for Robotic Object Recognition. IEEE Robotics and Automation Letters, 7(4), 9557–9564. https://doi.org/10.1109/LRA.2022.3191408
| Deep Active Cross-Modal Visuo-Tactile Transfer Learning for Robotic Object Recognition at reposiTUm , opens an external URL in a new window
Pantano, M., Pavlovskyi, Y., Schulenburg, E., Traganos, K., Ahmadi, S., Regulin, D., Lee, D., & Saenz, J. (2022). Novel Approach Using Risk Analysis Component to Continuously Update Collaborative Robotics Applications in the Smart, Connected Factory Model. Applied Sciences, 12(11), Article 5639. https://doi.org/10.3390/app12115639
| Novel Approach Using Risk Analysis Component to Continuously Update Collaborative Robotics Applications in the Smart, Connected Factory Model at reposiTUm , opens an external URL in a new window
Michel, Y., Ott, C., & Lee, D. (2022). Safety-Aware Hierarchical Passivity-Based Variable Compliance Control for Redundant Manipulators. IEEE Transactions on Robotics, 38(6), 3899–3916. https://doi.org/10.1109/TRO.2022.3174478
| Safety-Aware Hierarchical Passivity-Based Variable Compliance Control for Redundant Manipulators at reposiTUm , opens an external URL in a new window
An, S., Park, G., & Lee, D. (2022). When Prioritization Meets Input-output Linearization: A Prioritized Multi-objective Control and Case Study with Two-link Manipulator. In 0743-1546 (pp. 2560–2565). IEEE. https://doi.org/10.1109/CDC51059.2022.9992645
| When Prioritization Meets Input-output Linearization: A Prioritized Multi-objective Control and Case Study with Two-link Manipulator at reposiTUm , opens an external URL in a new window

Further Publications

Journal articles

Youssef Michel, Zhendong Li, and Dongheui Lee, A Learning Based Shared Control Approach For Contact Tasks, IEEE Robotics and Automation Letters (RA-L), pp. - , 2023. DOI: 10.1109/LRA.2023.3322332
Huang Dan, Hyemin Ahn, Shile Li, Yueming Hu, and Dongheui Lee, Estimation of 6D pose of objects based on a variant adversarial autoencoder, Neural Processing Letters, 2023

Conference contributions

Thomas Eiband, Florian Lay, Korbinian Nottensteiner, Dongheui Lee, Automatic Skill Recognition in a Knowledge-driven Robot Programming Framework, 5th International Conference on Industry 4.0 and Smart Manufacturing, 2023

Contact

Email: autonomous.systems@tuwien.ac.at

Address: Gusshausstrasse 27, 1040 Wien, opens an external URL in a new window

Socials

Youtube, opens an external URL in a new window

Contact

Email: autonomous.systems@tuwien.ac.at

Address: Gusshausstrasse 27, 1040 Wien, opens an external URL in a new window

Socials

Youtube, opens an external URL in a new window

Name	Purpose	Lifetime	Type	Provider
CookieConsent	Saves your settings for the use of cookies on this website.	1 year	HTML	Homepage TU Wien
SimpleSAML	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
SimpleSAMLAuthToken	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
fe_typo_user	Is needed so that in case of a Typo3 frontend login the session ID is recognized to grant access to protected areas.	session	HTTP	Homepage TU Wien
staticfilecache	Is needed to optimize the delivery time of the website.	session	HTTP	Homepage TU Wien
JESSIONSID	Is needed so that in case of a LectureTube the session ID is recognized to grant access to protected areas.	session	HTTP	LectureTube TU Wien
_shibsession_lecturetube	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	LectureTube TU Wien

Name	Purpose	Lifetime	Type	Provider
_pk_id	Used to store a few details about the user such as the unique visitor ID.	13 months	HTML	Matomo TU Wien
_pk_ref	Is used to store the information of the users home website.	6 months	HTML	Matomo TU Wien
_pk_ses	Is needed to store temporary data of the visit.	30 minutes	HTML	Matomo TU Wien
nmstat	Is used to record the behaviour on the website. It is used to collect statistics about website usage, such as when the visitor last visited the website. The cookie does not contain any personal data and is only used for website analysis.	1000 days	HTML	Siteimprove
siteimproveses	Is used to track the sequence of pages that a visitor views during his/her visit to the website. The cookie does not contain any personal data and is used solely for website analysis.	session	HTTP	Siteimprove
AWSELB	Always occurs in pairs with siteimproveses (for load balancing on the provider server)	session	HTTP	Siteimprove

Name	Purpose	Lifetime	Type	Provider
_ga	Is needed to distinguish the sessions of the users from each other.	persistent	HTTP	Google Analytics
_gali	Is needed to determine which links are clicked on a page.	expires immediately	HTTP	Google Analytics
_gat	This is a function-related cookie, whose tasks may differ.	2 years	HTTP	Google Analytics
_gid	Is needed to distinguish users and create statistics.	24 hours	HTTP	Google Analytics
_gads	Required to enable websites to display advertising from Google, including personalized advertising.	13 months	HTTP	Google Analytics
_gac_	Required by advertisers to measure user activity and the performance of their advertising campaigns.	90 days	HTTP	Google Analytics
_gcl_	Required by advertisers to determine how often users who click on their ads end up taking an action on their website.	90 days	HTTP	Google Analytics
_gcl_au	Contains a randomly generated user ID.	90 days	HTTP	Google
_gcl_aw	Is set when users click on a Google ad on the website and contains information about which ad was clicked.	90 days	HTTP	Google
__utma	Is used to record visits and visitors.	2 years	HTTP	Google Analytics
__utmb	Is used to detect new visits.	30 minutes	HTTP	Google Analytics
__utmc	Is used in connection with __utmb to determine whether it is a new (recent) visit.	session	HTTP	Google Analytics
__utmd	Is used to store and track visitor journeys through the site and classifies them into groups (marketing/tracking).	1 second	HTTP	Google Analytics
__utmt	Is needed to limit the query rate on Google Analytics.	10 minutes	HTTP	Google Analytics
__utmz	Is needed to determine from which source/campaign visitors come.	6 months	HTTP	Google Analytics
__utmvc	Is needed to collect information about user behavior on multiple websites. This information is used to optimize the relevance of advertising on the website.	24 hours	HTTP	Google AdSense
utm_source	Is needed to tag URLs with parameters to identify the campaigns that forward traffic.	expires immediately	HTTP	Google Analytics
__utm.gif	Is needed to save browser details.	session	HTTP	Google Analytics
gtag	Is needed to perform remarketing.	30 days	HTTP	Google AdSense
id	Is needed to perform remarketing.	2 years	HTTP	Google AdWords
1P_JAR	Is needed to optimize advertising, provide ads that are relevant to users, improve campaign performance reports, or prevent users from seeing the same ads more than once.	2 years	HTTP	Google
AID	Is needed to activate targeted advertising.	2 years	HTTP	Google Analytics
ANID	Is needed to display Google ads on non-Google websites.	2 years	HTTP	Google AdSense
APISID	Unknown functionality	2 years	HTTP	Google Ads Optimization
AR	Is needed to profile visitors' interests and display relevant ads on other websites. This cookie works by uniquely identifying your browser and device.	2 years	HTTP	Google AdSense
CONSENT	Is needed to store the preferences of visitors and personalize advertising.	persistent	HTTP	Google
DSID	Is needed by DoubleClick for advertising displayed in various places on the web and used to store the preferences of users.	2 years	HTTP	Doubleclick
DV	Is needed to store user preferences and other information. This includes, in particular, the preferred language, the number of search results to be displayed on the page, and the decision whether or not to activate the Google SafeSearch filter.	2 years	HTTP	Google
HSID	Contains the Google account ID and the last login time of the user.	2 years	HTTP	Google
IDE	Is needed by DoubleClick to record and report the actions of users on the website after viewing or clicking on one of the provider's ads, with the purpose of measuring the effectiveness of an advertisement and displaying targeted advertisements to users.	2 years	HTTP	Doubleclick
LOGIN_INFO	Is used to store the credentials of users of Google services.	2 years	HTTP	Google
NID	Is used to store information about user settings.	6 months	HTTP	Google
OTZ	Is needed to link activities of visitors with other devices that are previously logged in via the Google account. In this way, advertising is tailored to different devices.	1 month	HTTP	Google
RUL	Is needed by DoubleClick to determine whether advertising has been displayed correctly in order to make marketing activities more efficient.	1 year	HTTP	Doubleclick
SAPISID	Is needed by YouTube to store user settings and to calculate user bandwidth.	persistent	HTTP	Google
SEARCH_SAMESITE	Enables servers to mitigate the risk of CSRF and information leakage attacks by specifying that a particular cookie may only be sent on requests originating from the same registerable domain.	6 months	HTTP	Google
SID	Contains the Google account ID and the last login time of the user.	2 years	HTTP	Google
SIDCC	Is needed to store information about user settings and information for Google Maps.	3 months	HTTP	Google
SSID	Is needed to collect visitor information for videos hosted by YouTube on Google Maps integrated maps.	persistent	HTTP	Google
__SECURE-1PAPISID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-1PSID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-3PAPISID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-3PSID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-3PSIDCC	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-APISID	Is needed to profile the interests of website visitors in order to display relevant and personalized advertising through retargeting.	8 months	HTTP	Google
__SECURE-HSID	Is needed to secure digitally signed and encrypted data from the unique Google ID and to store the last login time that Google uses to identify visitors, prevent fraudulent use of login data, and protect visitor data from unauthorized parties. This may also be used for targeting purposes to display relevant and personalized advertising content.	8 months	HTTP	Google
__SECURE-SSID	Is needed to store information about how visitors use the site and about the ads they may have seen before visiting the site. Also used to customize ads on Google domains.	8 months	HTTP	Google
test_cookie	Is set as a test to check whether the browser allows cookies to be set. Does not contain any identification features.	15 minutes	HTTP	Google
VISITOR_INFO1_LIVE	Is needed by YouTube to store user settings and to calculate user bandwidth.	6 months	HTTP	Youtube
facebook	Is used to Enable ad delivery or retargeting	90 days	HTTP	Meta (Facebook)
__fb_chat_plugin	Is needed to store and track interactions (marketing/tracking).	persistent	HTTP	Meta (Facebook)
_js_datr	Is needed to save user settings.	2 years	HTTP	Meta (Facebook)
_fbc	Is needed to save the last visit (marketing/tracking).	2 years	HTTP	Meta (Facebook)
fbm	Is needed to store account data (marketing/tracking).	1 year	HTTP	Meta (Facebook)
xs	Is needed to store a unique session ID (marketing/tracking).	1 year	HTTP	Meta (Facebook)
wd	Is needed to log the screen resolution.	1 week	HTTP	Meta (Facebook)
fr	Is needed to serve ads and measure and improve their relevance.	3 months	HTTP	Meta (Facebook)
act	Is needed to store logged in users (marketing/tracking).	90 days	HTTP	Meta (Facebook)
_fbp	Is needed to store and track visits to various websites (marketing/tracking).	3 months	HTTP	Meta (Facebook)
datr	Is needed to identify the browser for security and website integrity purposes, including account recovery and identification of potentially compromised accounts.	2 years	HTTP	Meta (Facebook)
dpr	Is used for analysis purposes. Technical parameters are logged (e.g. aspect ratio and dimensions of the screen) so that Facebook apps can be displayed correctly.	1 week	HTTP	Meta (Facebook)
sb	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta (Facebook)
dbln	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta (Facebook)
spin	Is needed for promotional purposes and social campaign reporting.	session	HTTP	Meta (Facebook)
presence	Contains the "chat" status of logged in users.	1 month	HTTP	Meta (Facebook)
cppo	Is needed for statistical purposes.	90 days	HTTP	Meta (Facebook)
locale	Is needed to save the language settings.	session	HTTP	Meta (Facebook)
pl	Required for Facebook Pixel.	2 years	HTTP	Meta (Facebook)
lu	Required for Facebook Pixel.	2 years	HTTP	Meta (Facebook)
c_user	Required for Facebook Pixel.	3 months	HTTP	Meta (Facebook)
bcookie	Is needed to store browser data (marketing/tracking).	2 years	HTTP	LinkedIn
li_oatml	Is needed to identify LinkedIn members outside of LinkedIn for advertising and analytics purposes.	1 month	HTTP	LinkedIn
BizographicsOptOut	Is needed to save privacy settings.	10 years	HTTP	LinkedIn
li_sugr	Is needed to store browser data (marketing/tracking).	3 months	HTTP	LinkedIn
UserMatchHistory	Is needed to provide advertising or retargeting (marketing/tracking).	30 days	HTTP	LinkedIn
linkedin_oauth_	Is needed to provide cross-page functionality.	session	HTTP	LinkedIn
lidc	Is needed to store performed actions on the website (marketing/tracking).	1 day	HTTP	LinkedIn
bscookie	Is needed to store performed actions on the website (marketing/tracking).	2 years	HTTP	LinkedIn
X-LI-IDC	Is needed to provide cross-page functionality (marketing/tracking).	session	HTTP	LinkedIn
AnalyticsSyncHistory	Stores the time when the user was synchronized with the "lms_analytics" cookie.	30 days	HTTP	LinkedIn
lms_ads	Is needed to identify LinkedIn members outside of LinkedIn.	30 days	HTTP	LinkedIn
lms_analytics	Is needed to identify LinkedIn members for analytics purposes.	30 days	HTTP	LinkedIn
li_fat_id	Required for indirect member identification used for conversion tracking, retargeting and analytics.	30 days	HTTP	LinkedIn
U	Is needed to identify the browser.	3 months	HTTP	LinkedIn
_guid	Is needed to identify a LinkedIn member for advertising via Google Ads.	90 days	HTTP	LinkedIn

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