Till innehåll på sidan

Publikationer

Här listas avdelningens 50 senaste publikationer från KTH:s publikationsportal DiVA.

Länk till hela publikationslistan för RPL i DiVA hittas i botten av denna lista.

Publikationer av författare från RPL

[1]
[2]
F. Esposito et al., "Learning Task Constraints in Visual-Action Planning from Demonstrations," i 2021 30Th Ieee International Conference On Robot And Human Interactive Communication (Ro-Man), 2021, s. 131-138.
[3]
W. Yin et al., "Graph-based Normalizing Flow for Human Motion Generation and Reconstruction," i 2021 30th IEEE international conference on robot and human interactive communication (RO-MAN), 2021, s. 641-648.
[4]
S. Manzinger, C. Pek och M. Althoff, "Using Reachable Sets for Trajectory Planning of Automated Vehicles," IEEE Transactions on Intelligent Vehicles, vol. 6, no. 2, s. 232-248, 2021.
[5]
M. Ning et al., "YOLOv4-object : an Efficient Model and Method for Object Discovery," i 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), 2021, s. 31-36.
[7]
K. Andersson, "Improving Fixed Wing UAV Endurance, by Cooperative Autonomous Soaring," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:65, 2021.
[8]
P. Schillinger et al., "Adaptive heterogeneous multi-robot collaboration from formal task specifications," Robotics and Autonomous Systems, vol. 145, 2021.
[10]
D. Kragic och Y. Sandamirskaya, "Effective and natural human-robot interaction requires multidisciplinary research," SCIENCE ROBOTICS, vol. 6, no. 58, 2021.
[11]
M. C. Welle et al., "Partial caging : a clearance-based definition, datasets, and deep learning," Autonomous Robots, vol. 45, no. 5, s. 647-664, 2021.
[12]
A. Longhini et al., "Textile Taxonomy and Classification Using Pulling and Twisting," i IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) : Prague/Online 27.09-01.10.2021, 2021, s. 7541-7548.
[13]
T. Kucherenko, "Developing and evaluating co-speech gesture-synthesis models for embodied conversational agents," Doktorsavhandling : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:75, 2021.
[14]
R. Nagy et al., "A Framework for Integrating Gesture Generation Models into Interactive Conversational Agents," i 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS)., 2021.
[15]
M. C. Welle, "Learning Structured Representations for Rigid and Deformable Object Manipulation," Doktorsavhandling Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:72, 2021.
[16]
A. L. Gert et al., "COORDINATING WITH A ROBOT PARTNER AFFECTS ACTION MONITORING RELATED NEURAL PROCESSING," Psychophysiology, vol. 58, s. S60-S60, 2021.
[17]
M. M. N. Bienkiewicz et al., "Bridging the gap between emotion and joint action," Neuroscience and Biobehavioral Reviews, vol. 131, s. 806-833, 2021.
[18]
C. Chernik, P. Tajvar och J. Tumova, "Robust Feedback Motion Primitives for Exploration of Unknown Terrains," i IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.
[20]
U. Wennberg och G. E. Henter, "The Case for Translation-Invariant Self-Attention in Transformer-Based Language Models," i ACL-IJCNLP 2021 : THE 59TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 11TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING, VOL 2, 2021, s. 130-140.
[21]
C. Ceylan, S. Franzen och F. T. Pokorny, "Learning Node Representations Using Stationary Flow Prediction on Large Payment and Cash Transaction Networks," i International Conference On Machine Learning, Vol 139, 2021.
[22]
I. Torre et al., "Dimensional perception of a ‘smiling McGurkeffect’," i 2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII), 2021.
[23]
I. Torre et al., "Exploring the Effects of Virtual Agents’ Smiles on Human-Agent Interaction : A Mixed-Methods Study," i 2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII), 2021.
[24]
N. Masud, "About Physical Human Robotic Interaction for Assistive Exoskeletons," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2021:58, 2021.
[25]
H. Eivazi et al., "Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence," International Journal of Heat and Fluid Flow, vol. 90, 2021.
[26]
T. Kucherenko et al., "Speech2Properties2Gestures : Gesture-Property Prediction as a Tool for Generating Representational Gestures from Speech," i IVA '21 : Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents, 2021, s. 145-147.
[27]
S. van Waveren et al., "Exploring Non-Expert Robot Programming Through Crowdsourcing," Frontiers in Robotics and AI, vol. 8, 2021.
[28]
K. Grover et al., "Semantic Abstraction-Guided Motion Planning for scLTL Missions in Unknown Environments," i ROBOTICS : SCIENCE AND SYSTEM XVII, 2021.
[29]
A. Guemes et al., "From coarse wall measurements to turbulent velocity fields through deep learning," Physics of fluids, vol. 33, no. 7, 2021.
[30]
A. Czeszumski et al., "Coordinating With a Robot Partner Affects Neural Processing Related to Action Monitoring," Frontiers in Neurorobotics, vol. 15, 2021.
[31]
Ö. Özkahraman och P. Ögren, "Efficient Navigation Aware Seabed Coverage using AUVs," i Proceedings of 2021 IEEE International Conference on Safety, Security, and Rescue Robotics (SSRR), October 25-27 2021, New York, USA., 2021.
[32]
E. Morast och P. Jensfelt, "Towards Next Best View Planning for Time-Variant Scenes," i 2021 7th international conference on automation, robotics and applications (icara 2021), 2021, s. 247-252.
[33]
R. Bonnevie, D. Duberg och P. Jensfelt, "Long-Term Exploration in Unknown Dynamic Environments," i 2021 7Th International Conference On Automation, Robotics And Applications (Icara 2021), 2021, s. 32-37.
[34]
S. Abdul Khader, "Data-Driven Methods for Contact-Rich Manipulation: Control Stability and Data-Efficiency," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 49, 2021.
[35]
F. I. Dogan, "Social Robots That Understand Natural Language Instructions and Resolve Ambiguities," i RSS Pioneers 2021 - Held in conjunction with the main Robotics: Science and Systems (RSS) Conference, 2021, 2021.
[37]
[38]
P. H. Andersen et al., "Towards Machine Recognition of Facial Expressions of Pain in Horses," Animals, vol. 11, no. 6, 2021.
[39]
[40]
A. Linard et al., "Formalizing Trajectories in Human-Robot Encounters via Probabilistic STL Inference," i 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021.
[41]
I. Torre et al., "Should Robots Chicken? : How Anthropomorphism and Perceived Autonomy Influence Trajectories in a Game-Theoretic Problem," i Proceedings of the 2021 ACM/IEEE International Conference on Human-Robot Interaction, 2021, s. 370-379.
[42]
F. Esposito et al., "Learning Task Constraints in Visual-Action Planning from Demonstrations," i IEEE Int. Conf. on Robot and Human Interactive Communication, 2021.
[43]
H. Yin, A. Varava och D. Kragic, "Modeling, learning, perception, and control methods for deformable object manipulation," Science Robotics, vol. 6, no. 54, 2021.
[44]
C. Pek, "Discrimination through algorithms and AI: Technical aspects," i Künstliche Intelligenz : Recht und Praxis automatisierter und autonomer Systeme, Kuuya Josef Chibanguza, Christian Kuß and Hans Steege red., : Nomos Verlagsgesellschaft, 2021.
[45]
T. Kucherenko et al., "A large, crowdsourced evaluation of gesture generation systems on common data : The GENEA Challenge 2020," i Proceedings IUI '21: 26th International Conference on Intelligent User Interfaces, 2021, s. 11-21.
[46]
R. Gieselmann och F. T. Pokorny, "Planning-Augmented Hierarchical Reinforcement Learning," IEEE Robotics and Automation Letters, vol. 6, no. 3, s. 5097-5104, 2021.
[47]
T. Nyberg et al., "Risk-aware Motion Planning for Autonomous Vehicles with Safety Specifications," i 32nd IEEE Intelligent Vehicles Symposium, July 11-17, 2021 Nagoya University, Nagoya, Japan [Virtual], 2021.
[48]
S. Bujwid och J. Sullivan, "Large-Scale Zero-Shot Image Classification from Rich and Diverse Textual Descriptions," i Proceedings of the Third Workshop on Beyond Vision and LANguage : inTEgrating Real-world kNowledge (LANTERN), 2021, s. 38-52.
[49]
E. Heiden et al., "Bench-MR : A Motion Planning Benchmark for Wheeled Mobile Robots," IEEE Robotics and Automation Letters, vol. 6, no. 3, s. 4536-4543, 2021.
[50]
M. Lee et al., "Robo-Identity: Exploring Artificial Identity and Multi-Embodiment," i ACM/IEEE International Conference on Human-Robot Interaction, 2021.
Fullständig lista i KTH:s publikationsportal